SlideShare a Scribd company logo
Introduction to
Decision Trees
14
A decision tree can be used as a model for a sequential decision problems under uncertainty. A
decision tree describes graphically the decisions to be made, the events that may occur, and the
outcomes associated with combinations of decisions and events. Probabilities are assigned to the
events, and values are determined for each outcome. A major goal of the analysis is to determine
the best decisions.
14.1 DECISION TREE STRUCTURE
Decision tree models include such concepts as nodes, branches, terminal values, strategy, payoff
distribution, certain equivalent, and the rollback method. The following problem illustrates the
basic concepts.
DriveTek Problem, Part A
DriveTek Research Institute discovers that a computer company wants a new storage device for a
proposed new computer system. Since the computer company does not have research people
available to develop the new storage device, it will subcontract the development to an independent
research firm. The computer company has offered a fixed fee for the best proposal for developing
the new storage device. The contract will go to the firm with the best technical plan and the
highest reputation for technical competence.
DriveTek Research Institute wants to enter the competition. Management estimates a moderate
cost for preparing a proposal, but they are concerned that they may not win the contract.
If DriveTek decides to prepare a proposal, and if they win the contract, their engineers are not sure
about how they will develop the storage device. They are considering three alternative approaches.
The first approach is a very expensive mechanical method, and the engineers are certain they can
develop a successful model with this approach. A second approach involves electronic
components. The engineers think that the electronic approach is a relatively inexpensive method
for developing a model of the storage device, but they are not sure that the results will be
satisfactory for satisfying the contract. A third inexpensive approach uses magnetic components.
This magnetic method costs more than the electronic method, and the engineers think that it has a
higher chance of success.
DriveTek Research can work on only one approach at a time and has time to try only two
approaches. If it tries either the magnetic or electronic method and the attempt fails, the second
choice must be the mechanical method to guarantee a successful model.
The management of DriveTek Research needs help in incorporating this information into a
decision to proceed or not.
158 Chapter 14 Introduction to Decision Trees
Nodes and Branches
Decision trees have three kinds of nodes and two kinds of branches. A decision node is a point
where a choice must be made; it is shown as a square. The branches extending from a decision
node are decision branches, each branch representing one of the possible alternatives or courses of
action available at that point. The set of alternatives must be mutually exclusive (if one is chosen,
the others cannot be chosen) and collectively exhaustive (all possible alternatives must be included
in the set).
There are two major decisions in the DriveTek problem. First, the company must decide whether
or not to prepare a proposal. Second, if it prepares a proposal and is awarded the contract, it must
decide which of the three approaches to try to satisfy the contract.
An event node is a point where uncertainty is resolved (a point where the decision maker learns
about the occurrence of an event). An event node, sometimes called a "chance node," is shown as
a circle. The event set consists of the event branches extending from an event node, each branch
representing one of the possible events that may occur at that point. The set of events must be
mutually exclusive (if one occurs, the others cannot occur) and collectively exhaustive (all
possible events must be included in the set). Each event is assigned a subjective probability; the
sum of probabilities for the events in a set must equal one.
The three sources of uncertainty in the DriveTek problem are: whether it is awarded the contract
or not, whether the electronic approach succeeds or fails, and whether the magnetic approach
succeeds or fails.
In general, decision nodes and branches represent the controllable factors in a decision problem;
event nodes and branches represent uncontrollable factors.
Decision nodes and event nodes are arranged in order of subjective chronology. For example, the
position of an event node corresponds to the time when the decision maker learns the outcome of
the event (not necessarily when the event occurs).
The third kind of node is a terminal node, representing the final result of a combination of
decisions and events. Terminal nodes are the endpoints of a decision tree, shown as the end of a
branch on hand-drawn diagrams and as a triangle or vertical bar on computer-generated diagrams.
The following table shows the three kinds of nodes and two kinds of branches used to represent a
decision tree.
Figure 14.1 Nodes and Symbols
Type of Node Written Symbol Computer Symbol Node Successor
Decision square square decision branches
Event circle circle event branches
Terminal endpoint triangle or bar terminal value
In the DriveTek problem, the first portion of the decision tree is shown in Figure 14.2.
14.1 Decision Tree Structure 159
Figure 14.2 DriveTek Initial Decision and Event
Awarded contract
Prepare proposal
Not awarded contract
Don't prepare proposal
If DriveTek is awarded the contract, they must decide which approach to use. For the electronic
and magnetic approaches, the result is uncertain, as shown in Figure 14.3. The arrangement of the
decision and event branches is called the structure of the decision tree.
Figure 14.3 DriveTek Decisions and Events (Structure)
Use mechanical method
Electronic success
Try electronic method
Awarded contract
Electronic failure
Magnetic success
Prepare proposal
Try magnetic method
Magnetic failure
Not awarded contract
Don't prepare proposal
For representing a sequential decision problem, the tree diagram is usually better than the written
description. In some decision problems, the choice may be obvious by looking at the diagram.
That is, the decision maker may know enough about the desirability of the outcomes (endpoints in
the tree) and how likely they are. But usually the next step in the analysis after documenting the
structure is to assign values to the endpoints.
160 Chapter 14 Introduction to Decision Trees
14.2 DECISION TREE TERMINAL VALUES
Each terminal node has an associated terminal value, sometimes called a payoff value, outcome
value, or endpoint value. Each terminal value measures the result of a scenario: the sequence of
decisions and events on a unique path leading from the initial decision node to a specific terminal
node. To determine the terminal value, one approach assigns a cash flow value to each decision
branch and event branch and then sums the cash flow values on the branches leading to a terminal
node to determine the terminal value. Some problems require a more elaborate value model to
determine the terminal values.
DriveTek Problem, Part B
DriveTek thinks it will cost $50,000 to prepare a proposal. If they are awarded the contract,
DriveTek will receive an immediate payment of $250,000. The engineers think that the sure-
success mechanical method will cost $120,000. The possibly-successful electronic approach will
cost $50,000, and the more-likely-successful magnetic approach will cost $80,000. In the
DriveTek problem, these distinct cash flows associated with many of the decision and event
branches are shown in Figure 14.4.
Figure 14.4 DriveTek Cash Flows and Outcome Values
Use mechanical method
$80,000
-$120,000
Electronic success
$150,000
Try electronic method $0
Awarded contract
-$50,000
$250,000 Electronic failure
$30,000
-$120,000
Magnetic success
Prepare proposal $120,000
Try magnetic method $0
-$50,000
-$80,000
Magnetic failure
$0
-$120,000
Not awarded contract
-$50,000
$0
Don't prepare proposal
$0
$0
Figure 14.4 also shows the sum of branch cash flows at the endpoints. For example, the $30,000
terminal value on the far right of the diagram is associated with the scenario shown in Figure 14.5.
Figure 14.5 Terminal Value for a Scenario
Branch Type Branch Name Cash Flow
Decision Prepare proposal –$50,000
Event Awarded contract +$250,000
Decision Try electronic method –$50,000
Event Electronic failure (Use mechanical method) –$120,000
Terminal value = +$30,000
14.3 Decision Tree Probabilities 161
14.3 DECISION TREE PROBABILITIES
DriveTek Problem, Part C
DriveTek management thinks there is a fifty-fifty chance of winning the contract. The engineers
think that the inexpensive electronic method has only a 50% chance of satisfactory results. In their
opinion the somewhat more costly magnetic method has 70% chance of success.
Figure 14.6 DriveTek Complete Decision Tree Model
Use mechanical method
$80,000
0.5
Electronic success
$150,000
0.5 Try electronic method
Awarded contract
0.5
Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal $120,000
Try magnetic method
0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
Figure 14.6 is a complete decision tree model.
14.4 ROLLBACK METHOD
If we have a method for determining certain equivalents (expected values for a risk neutral
decision maker), we don't need to examine every possible strategy explicitly. Instead, the method
known as rollback determines the single best strategy.
The rollback algorithm, sometimes called backward induction or "average out and fold back,"
starts at the terminal nodes of the tree and works backward to the initial decision node,
determining the certain equivalent rollback values for each node. Rollback values are determined
as follows:
• At a terminal node, the rollback value equals the terminal value.
• At an event node, the rollback value for a risk neutral decision maker is determined using
expected value (probability-weighted average); the branch probability is multiplied times
the successor rollback value, and the products are summed.
162 Chapter 14 Introduction to Decision Trees
• At a decision node, the rollback value is set equal to the highest rollback value on the
immediate successor nodes.
In TreePlan tree diagrams the rollback values are located to the left and below each decision,
event, and terminal node. Terminal values and rollback values for the DriveTek problem are
shown below.
Figure 14.7 Terminal Node Rollback Values
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
0.5
Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
14.4 Rollback Method 163
Figure 14.8 Electronic Event Node Rollback Value
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
Figure 14.9 Magnetic Event Node Rollback Value
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$84,000 0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
At the event node following "Try electronic method," compute an expected value (probability-
weighted average):
= 0.5*150,000 + 0.5*30,000
= 75,000 + 15,000
= 90,000
164 Chapter 14 Introduction to Decision Trees
At the event node following "Try magnetic method," compute an expected value:
= 0.7*120,000 + 0.3*0
= 84,000 + 0
= 84,000
Figure 14.10 Method Decision Node Rollback Value
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$84,000 0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
At the decision node following "Awarded contract," choose the highest successor rollback value:
= Max($80,000, $90,000, $84,000)
= $90,000
14.4 Rollback Method 165
Figure 14.11 Contract Event Node Rollback Value
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$20,000
$84,000 0.3
Magnetic failure
$0
0.5
Not awarded contract
-$50,000
Don't prepare proposal
$0
At the event node following "Prepare proposal," compute an expected value:
= 0.5*90,000 + 0.5*(–50,000)
= 45,000 + (–25,000)
= 20,000
Figure 14.12 Proposal Decision Node Rollback Value
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$20,000
$84,000 0.3
Magnetic failure
$0
0.5
$20,000 Not awarded contract
-$50,000
Don't prepare proposal
$0
166 Chapter 14 Introduction to Decision Trees
At the initial decision node, choose the highest successor rollback value:
= Max($20,000, $0)
= $20,000
Figure 14.13 Rollback Optimal Choices
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$20,000
$84,000 0.3
Magnetic failure
$0
0.5
$20,000 Not awarded contract
-$50,000
Don't prepare proposal
$0
At the initial decision node, choose "Prepare proposal."
If "Awarded contract," choose "Try electronic method."
14.4 Rollback Method 167
Figure 14.14 Rollback Optimal Strategy Branches and Payoffs
Use mechanical method
$80,000
0.5
Electronic success
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
0.7
Magnetic success
Prepare proposal
Try magnetic method $120,000
$20,000
$84,000 0.3
Magnetic failure
$0
0.5
$20,000 Not awarded contract
-$50,000
Don't prepare proposal
$0
Using the best choices at decision nodes (controllable) and depending on what happens at the
event nodes (uncontrollable), there are three possible outcomes.
Figure 14.15 All Rollback Values
Use mechanical method
$80,000
$80,000
0.5
Electronic success
$150,000
0.5 Try electronic method $150,000
Awarded contract
$90,000 0.5
$90,000 Electronic failure
$30,000
$30,000
0.7
Magnetic success
Prepare proposal $120,000
Try magnetic method $120,000
$20,000
$84,000 0.3
Magnetic failure
$0
$0
0.5
$20,000 Not awarded contract
-$50,000
-$50,000
Don't prepare proposal
$0
$0
168 Chapter 14 Introduction to Decision Trees
Optimal Strategy
After the rollback method has determined certain equivalents for each node, the optimal strategy
can be identified by working forward through the tree. At the initial decision node, the $20,000
rollback value equals the rollback value of the "Prepare proposal" branch, indicating the
alternative that should be chosen. DriveTek will either be awarded the contract or not; there is a
subsequent decision only if DriveTek obtains the contract. (In a more complicated decision tree,
the optimal strategy must include decision choices for all decision nodes that might be
encountered.) At the decision node following "Awarded contract," the $90,000 rollback value
equals the rollback value of the "Try electronic method" branch, indicating the alternative that
should be chosen. Subsequently, if the electronic method fails, DriveTek must use the mechanical
method to satisfy the contract.
14.5 NEWOX DECISION TREE PROBLEM
The Newox Company is considering whether or not to drill for natural gas on its own land. If they
drill, their initial expenditure will be $40,000 for drilling costs. If they strike gas, they must spend
an additional $30,000 to cap the well and provide the necessary hardware and control equipment.
(This $30,000 cost is not a decision; it is associated with the event "strike gas.") If they decide to
drill but no gas is found, there are no other subsequent alternatives, so their outcome value is
$-40,000.
If they drill and find gas, there are two alternatives. Newox could sell to West Gas, which has
made a standing offer of $200,000 to purchase all rights to the gas well's production (assuming
that Newox has actually found gas). Alternatively, if gas is found, Newox can decide to keep the
well instead of selling to West Gas; in this case Newox manages the gas production and takes its
chances by selling the gas on the open market.
At the current price of natural gas, if gas is found it would have a value of $150,000 on the open
market. However, there is a possibility that the price of gas will rise to double its current value, in
which case a successful well will be worth $300,000.
The company's engineers feel that the chance of finding gas is 30 percent; their staff economist
thinks there is a 60 percent chance that the price of gas will double.

More Related Content

Similar to introduction-to-decision-trees.pdf

IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment ProblemIRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
IRJET Journal
 
dss
dssdss
Accident Prediction System Using Machine Learning
Accident Prediction System Using Machine LearningAccident Prediction System Using Machine Learning
Accident Prediction System Using Machine Learning
IRJET Journal
 
Invited presentation to 2003 RAeS Aerodynamics research conference
Invited presentation to 2003 RAeS Aerodynamics research conferenceInvited presentation to 2003 RAeS Aerodynamics research conference
Invited presentation to 2003 RAeS Aerodynamics research conference
stephen_mcparlin
 
Operation Research Techniques
Operation Research Techniques Operation Research Techniques
Operation Research Techniques
Lijin Mathew
 
report.pdf
report.pdfreport.pdf
report.pdf
KarnaPatel17
 
Operations Research Digital Material.pdf
Operations Research Digital Material.pdfOperations Research Digital Material.pdf
Operations Research Digital Material.pdf
TANVEERSINGHSOLANKI
 
Cost Analysis of ComFrame: A Communication Framework for Data Management in ...
Cost Analysis of ComFrame: A Communication Framework for  Data Management in ...Cost Analysis of ComFrame: A Communication Framework for  Data Management in ...
Cost Analysis of ComFrame: A Communication Framework for Data Management in ...
IOSR Journals
 
Quantitative management
Quantitative managementQuantitative management
Quantitative management
smumbahelp
 
Iaetsd performance voting algorithms for software safety
Iaetsd performance voting algorithms for software safetyIaetsd performance voting algorithms for software safety
Iaetsd performance voting algorithms for software safety
Iaetsd Iaetsd
 
3D Functional Tolerancing And Annotation CATIA
3D Functional Tolerancing And Annotation CATIA3D Functional Tolerancing And Annotation CATIA
3D Functional Tolerancing And Annotation CATIA
Leslie Schulte
 
Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
 Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj... Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
SEAA 2022
 
Identification of parameters of an induction motor from field solution 9 11 n...
Identification of parameters of an induction motor from field solution 9 11 n...Identification of parameters of an induction motor from field solution 9 11 n...
Identification of parameters of an induction motor from field solution 9 11 n...
Valentino Selayan
 
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms ComparisonIRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET Journal
 
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms ComparisonIRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET Journal
 
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTIONGRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
IJCSEA Journal
 
Chapter1 introduction-to-design
Chapter1 introduction-to-designChapter1 introduction-to-design
Chapter1 introduction-to-design
Vin Voro
 
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
maikelcorleoni
 

Similar to introduction-to-decision-trees.pdf (18)

IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment ProblemIRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
IRJET- Comparison for Max-Flow Min-Cut Algorithms for Optimal Assignment Problem
 
dss
dssdss
dss
 
Accident Prediction System Using Machine Learning
Accident Prediction System Using Machine LearningAccident Prediction System Using Machine Learning
Accident Prediction System Using Machine Learning
 
Invited presentation to 2003 RAeS Aerodynamics research conference
Invited presentation to 2003 RAeS Aerodynamics research conferenceInvited presentation to 2003 RAeS Aerodynamics research conference
Invited presentation to 2003 RAeS Aerodynamics research conference
 
Operation Research Techniques
Operation Research Techniques Operation Research Techniques
Operation Research Techniques
 
report.pdf
report.pdfreport.pdf
report.pdf
 
Operations Research Digital Material.pdf
Operations Research Digital Material.pdfOperations Research Digital Material.pdf
Operations Research Digital Material.pdf
 
Cost Analysis of ComFrame: A Communication Framework for Data Management in ...
Cost Analysis of ComFrame: A Communication Framework for  Data Management in ...Cost Analysis of ComFrame: A Communication Framework for  Data Management in ...
Cost Analysis of ComFrame: A Communication Framework for Data Management in ...
 
Quantitative management
Quantitative managementQuantitative management
Quantitative management
 
Iaetsd performance voting algorithms for software safety
Iaetsd performance voting algorithms for software safetyIaetsd performance voting algorithms for software safety
Iaetsd performance voting algorithms for software safety
 
3D Functional Tolerancing And Annotation CATIA
3D Functional Tolerancing And Annotation CATIA3D Functional Tolerancing And Annotation CATIA
3D Functional Tolerancing And Annotation CATIA
 
Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
 Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj... Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
Model-Driven Optimization: Generating Smart Mutation Operators for Multi-Obj...
 
Identification of parameters of an induction motor from field solution 9 11 n...
Identification of parameters of an induction motor from field solution 9 11 n...Identification of parameters of an induction motor from field solution 9 11 n...
Identification of parameters of an induction motor from field solution 9 11 n...
 
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms ComparisonIRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms Comparison
 
IRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms ComparisonIRJET- Supervised Learning Classification Algorithms Comparison
IRJET- Supervised Learning Classification Algorithms Comparison
 
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTIONGRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
GRID COMPUTING: STRATEGIC DECISION MAKING IN RESOURCE SELECTION
 
Chapter1 introduction-to-design
Chapter1 introduction-to-designChapter1 introduction-to-design
Chapter1 introduction-to-design
 
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
Multi-Period Integer Portfolio Optimization Using a Quantum Annealer (Present...
 

Recently uploaded

ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
HannahDy7
 
PrudentRx: A Resource for Patient Education and Engagement
PrudentRx: A Resource for Patient Education and EngagementPrudentRx: A Resource for Patient Education and Engagement
PrudentRx: A Resource for Patient Education and Engagement
PrudentRx Program
 
The Importance of Black Women Understanding the Chemicals in Their Personal C...
The Importance of Black Women Understanding the Chemicals in Their Personal C...The Importance of Black Women Understanding the Chemicals in Their Personal C...
The Importance of Black Women Understanding the Chemicals in Their Personal C...
bkling
 
Get Covid Testing at Fit to Fly PCR Test
Get Covid Testing at Fit to Fly PCR TestGet Covid Testing at Fit to Fly PCR Test
Get Covid Testing at Fit to Fly PCR Test
NX Healthcare
 
Vicarious movements or trick movements_AB.pdf
Vicarious movements or trick movements_AB.pdfVicarious movements or trick movements_AB.pdf
Vicarious movements or trick movements_AB.pdf
Arunima620542
 
Top Rated Massage Center In Ajman Chandrima Spa
Top Rated Massage Center In Ajman Chandrima SpaTop Rated Massage Center In Ajman Chandrima Spa
Top Rated Massage Center In Ajman Chandrima Spa
Chandrima Spa Ajman
 
Sexual Disorders.gender identity disorderspptx
Sexual Disorders.gender identity  disorderspptxSexual Disorders.gender identity  disorderspptx
Sexual Disorders.gender identity disorderspptx
Pupayumnam1
 
Hypertension and it's role of physiotherapy in it.
Hypertension and it's role of physiotherapy in it.Hypertension and it's role of physiotherapy in it.
Hypertension and it's role of physiotherapy in it.
Vishal kr Thakur
 
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
SGRT Community
 
Mental Health and Physical Wellbeing.pdf
Mental Health and Physical Wellbeing.pdfMental Health and Physical Wellbeing.pdf
Mental Health and Physical Wellbeing.pdf
shindesupriya013
 
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
Ear Solutions (ESPL)
 
National Rural Health Mission(NRHM).pptx
National Rural Health Mission(NRHM).pptxNational Rural Health Mission(NRHM).pptx
National Rural Health Mission(NRHM).pptx
Jyoti Chand
 
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Levi Shapiro
 
Hypotension and role of physiotherapy in it
Hypotension and role of physiotherapy in itHypotension and role of physiotherapy in it
Hypotension and role of physiotherapy in it
Vishal kr Thakur
 
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSONNEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
SHAMIN EABENSON
 
Professional Secrecy: Forensic Medicine Lecture
Professional Secrecy: Forensic Medicine LectureProfessional Secrecy: Forensic Medicine Lecture
Professional Secrecy: Forensic Medicine Lecture
DIVYANSHU740006
 
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdfU Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
Jokerwigs arts and craft
 
Pediatric Emergency Care for Children | Apollo Hospital
Pediatric Emergency Care for Children | Apollo HospitalPediatric Emergency Care for Children | Apollo Hospital
Pediatric Emergency Care for Children | Apollo Hospital
Apollo 24/7 Adult & Paediatric Emergency Services
 
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
Lighthouse Retreat
 
Sectional dentures for microstomia patients.pptx
Sectional dentures for microstomia patients.pptxSectional dentures for microstomia patients.pptx
Sectional dentures for microstomia patients.pptx
SatvikaPrasad
 

Recently uploaded (20)

ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
ilide.info-assessment-of-renal-and-urinary-tract-function-pr_1aae1860e4cff0a4...
 
PrudentRx: A Resource for Patient Education and Engagement
PrudentRx: A Resource for Patient Education and EngagementPrudentRx: A Resource for Patient Education and Engagement
PrudentRx: A Resource for Patient Education and Engagement
 
The Importance of Black Women Understanding the Chemicals in Their Personal C...
The Importance of Black Women Understanding the Chemicals in Their Personal C...The Importance of Black Women Understanding the Chemicals in Their Personal C...
The Importance of Black Women Understanding the Chemicals in Their Personal C...
 
Get Covid Testing at Fit to Fly PCR Test
Get Covid Testing at Fit to Fly PCR TestGet Covid Testing at Fit to Fly PCR Test
Get Covid Testing at Fit to Fly PCR Test
 
Vicarious movements or trick movements_AB.pdf
Vicarious movements or trick movements_AB.pdfVicarious movements or trick movements_AB.pdf
Vicarious movements or trick movements_AB.pdf
 
Top Rated Massage Center In Ajman Chandrima Spa
Top Rated Massage Center In Ajman Chandrima SpaTop Rated Massage Center In Ajman Chandrima Spa
Top Rated Massage Center In Ajman Chandrima Spa
 
Sexual Disorders.gender identity disorderspptx
Sexual Disorders.gender identity  disorderspptxSexual Disorders.gender identity  disorderspptx
Sexual Disorders.gender identity disorderspptx
 
Hypertension and it's role of physiotherapy in it.
Hypertension and it's role of physiotherapy in it.Hypertension and it's role of physiotherapy in it.
Hypertension and it's role of physiotherapy in it.
 
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
Surface guided deep inspiration breath hold (SG-DIBH) in ultra-hypofractionat...
 
Mental Health and Physical Wellbeing.pdf
Mental Health and Physical Wellbeing.pdfMental Health and Physical Wellbeing.pdf
Mental Health and Physical Wellbeing.pdf
 
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
Exploring the Benefits of Binaural Hearing: Why Two Hearing Aids Are Better T...
 
National Rural Health Mission(NRHM).pptx
National Rural Health Mission(NRHM).pptxNational Rural Health Mission(NRHM).pptx
National Rural Health Mission(NRHM).pptx
 
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
Michigan HealthTech Market Map 2024 with Policy Makers, Academic Innovation C...
 
Hypotension and role of physiotherapy in it
Hypotension and role of physiotherapy in itHypotension and role of physiotherapy in it
Hypotension and role of physiotherapy in it
 
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSONNEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
NEEDLE STICK INJURY - JOURNAL CLUB PRESENTATION - DR SHAMIN EABENSON
 
Professional Secrecy: Forensic Medicine Lecture
Professional Secrecy: Forensic Medicine LectureProfessional Secrecy: Forensic Medicine Lecture
Professional Secrecy: Forensic Medicine Lecture
 
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdfU Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
U Part Wigs_ A Natural Look with Minimal Effort Jokerwigs.in.pdf
 
Pediatric Emergency Care for Children | Apollo Hospital
Pediatric Emergency Care for Children | Apollo HospitalPediatric Emergency Care for Children | Apollo Hospital
Pediatric Emergency Care for Children | Apollo Hospital
 
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
Psychedelic Retreat Portugal - Escape to Lighthouse Retreats for an unforgett...
 
Sectional dentures for microstomia patients.pptx
Sectional dentures for microstomia patients.pptxSectional dentures for microstomia patients.pptx
Sectional dentures for microstomia patients.pptx
 

introduction-to-decision-trees.pdf

  • 1. Introduction to Decision Trees 14 A decision tree can be used as a model for a sequential decision problems under uncertainty. A decision tree describes graphically the decisions to be made, the events that may occur, and the outcomes associated with combinations of decisions and events. Probabilities are assigned to the events, and values are determined for each outcome. A major goal of the analysis is to determine the best decisions. 14.1 DECISION TREE STRUCTURE Decision tree models include such concepts as nodes, branches, terminal values, strategy, payoff distribution, certain equivalent, and the rollback method. The following problem illustrates the basic concepts. DriveTek Problem, Part A DriveTek Research Institute discovers that a computer company wants a new storage device for a proposed new computer system. Since the computer company does not have research people available to develop the new storage device, it will subcontract the development to an independent research firm. The computer company has offered a fixed fee for the best proposal for developing the new storage device. The contract will go to the firm with the best technical plan and the highest reputation for technical competence. DriveTek Research Institute wants to enter the competition. Management estimates a moderate cost for preparing a proposal, but they are concerned that they may not win the contract. If DriveTek decides to prepare a proposal, and if they win the contract, their engineers are not sure about how they will develop the storage device. They are considering three alternative approaches. The first approach is a very expensive mechanical method, and the engineers are certain they can develop a successful model with this approach. A second approach involves electronic components. The engineers think that the electronic approach is a relatively inexpensive method for developing a model of the storage device, but they are not sure that the results will be satisfactory for satisfying the contract. A third inexpensive approach uses magnetic components. This magnetic method costs more than the electronic method, and the engineers think that it has a higher chance of success. DriveTek Research can work on only one approach at a time and has time to try only two approaches. If it tries either the magnetic or electronic method and the attempt fails, the second choice must be the mechanical method to guarantee a successful model. The management of DriveTek Research needs help in incorporating this information into a decision to proceed or not.
  • 2. 158 Chapter 14 Introduction to Decision Trees Nodes and Branches Decision trees have three kinds of nodes and two kinds of branches. A decision node is a point where a choice must be made; it is shown as a square. The branches extending from a decision node are decision branches, each branch representing one of the possible alternatives or courses of action available at that point. The set of alternatives must be mutually exclusive (if one is chosen, the others cannot be chosen) and collectively exhaustive (all possible alternatives must be included in the set). There are two major decisions in the DriveTek problem. First, the company must decide whether or not to prepare a proposal. Second, if it prepares a proposal and is awarded the contract, it must decide which of the three approaches to try to satisfy the contract. An event node is a point where uncertainty is resolved (a point where the decision maker learns about the occurrence of an event). An event node, sometimes called a "chance node," is shown as a circle. The event set consists of the event branches extending from an event node, each branch representing one of the possible events that may occur at that point. The set of events must be mutually exclusive (if one occurs, the others cannot occur) and collectively exhaustive (all possible events must be included in the set). Each event is assigned a subjective probability; the sum of probabilities for the events in a set must equal one. The three sources of uncertainty in the DriveTek problem are: whether it is awarded the contract or not, whether the electronic approach succeeds or fails, and whether the magnetic approach succeeds or fails. In general, decision nodes and branches represent the controllable factors in a decision problem; event nodes and branches represent uncontrollable factors. Decision nodes and event nodes are arranged in order of subjective chronology. For example, the position of an event node corresponds to the time when the decision maker learns the outcome of the event (not necessarily when the event occurs). The third kind of node is a terminal node, representing the final result of a combination of decisions and events. Terminal nodes are the endpoints of a decision tree, shown as the end of a branch on hand-drawn diagrams and as a triangle or vertical bar on computer-generated diagrams. The following table shows the three kinds of nodes and two kinds of branches used to represent a decision tree. Figure 14.1 Nodes and Symbols Type of Node Written Symbol Computer Symbol Node Successor Decision square square decision branches Event circle circle event branches Terminal endpoint triangle or bar terminal value In the DriveTek problem, the first portion of the decision tree is shown in Figure 14.2.
  • 3. 14.1 Decision Tree Structure 159 Figure 14.2 DriveTek Initial Decision and Event Awarded contract Prepare proposal Not awarded contract Don't prepare proposal If DriveTek is awarded the contract, they must decide which approach to use. For the electronic and magnetic approaches, the result is uncertain, as shown in Figure 14.3. The arrangement of the decision and event branches is called the structure of the decision tree. Figure 14.3 DriveTek Decisions and Events (Structure) Use mechanical method Electronic success Try electronic method Awarded contract Electronic failure Magnetic success Prepare proposal Try magnetic method Magnetic failure Not awarded contract Don't prepare proposal For representing a sequential decision problem, the tree diagram is usually better than the written description. In some decision problems, the choice may be obvious by looking at the diagram. That is, the decision maker may know enough about the desirability of the outcomes (endpoints in the tree) and how likely they are. But usually the next step in the analysis after documenting the structure is to assign values to the endpoints.
  • 4. 160 Chapter 14 Introduction to Decision Trees 14.2 DECISION TREE TERMINAL VALUES Each terminal node has an associated terminal value, sometimes called a payoff value, outcome value, or endpoint value. Each terminal value measures the result of a scenario: the sequence of decisions and events on a unique path leading from the initial decision node to a specific terminal node. To determine the terminal value, one approach assigns a cash flow value to each decision branch and event branch and then sums the cash flow values on the branches leading to a terminal node to determine the terminal value. Some problems require a more elaborate value model to determine the terminal values. DriveTek Problem, Part B DriveTek thinks it will cost $50,000 to prepare a proposal. If they are awarded the contract, DriveTek will receive an immediate payment of $250,000. The engineers think that the sure- success mechanical method will cost $120,000. The possibly-successful electronic approach will cost $50,000, and the more-likely-successful magnetic approach will cost $80,000. In the DriveTek problem, these distinct cash flows associated with many of the decision and event branches are shown in Figure 14.4. Figure 14.4 DriveTek Cash Flows and Outcome Values Use mechanical method $80,000 -$120,000 Electronic success $150,000 Try electronic method $0 Awarded contract -$50,000 $250,000 Electronic failure $30,000 -$120,000 Magnetic success Prepare proposal $120,000 Try magnetic method $0 -$50,000 -$80,000 Magnetic failure $0 -$120,000 Not awarded contract -$50,000 $0 Don't prepare proposal $0 $0 Figure 14.4 also shows the sum of branch cash flows at the endpoints. For example, the $30,000 terminal value on the far right of the diagram is associated with the scenario shown in Figure 14.5. Figure 14.5 Terminal Value for a Scenario Branch Type Branch Name Cash Flow Decision Prepare proposal –$50,000 Event Awarded contract +$250,000 Decision Try electronic method –$50,000 Event Electronic failure (Use mechanical method) –$120,000 Terminal value = +$30,000
  • 5. 14.3 Decision Tree Probabilities 161 14.3 DECISION TREE PROBABILITIES DriveTek Problem, Part C DriveTek management thinks there is a fifty-fifty chance of winning the contract. The engineers think that the inexpensive electronic method has only a 50% chance of satisfactory results. In their opinion the somewhat more costly magnetic method has 70% chance of success. Figure 14.6 DriveTek Complete Decision Tree Model Use mechanical method $80,000 0.5 Electronic success $150,000 0.5 Try electronic method Awarded contract 0.5 Electronic failure $30,000 0.7 Magnetic success Prepare proposal $120,000 Try magnetic method 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0 Figure 14.6 is a complete decision tree model. 14.4 ROLLBACK METHOD If we have a method for determining certain equivalents (expected values for a risk neutral decision maker), we don't need to examine every possible strategy explicitly. Instead, the method known as rollback determines the single best strategy. The rollback algorithm, sometimes called backward induction or "average out and fold back," starts at the terminal nodes of the tree and works backward to the initial decision node, determining the certain equivalent rollback values for each node. Rollback values are determined as follows: • At a terminal node, the rollback value equals the terminal value. • At an event node, the rollback value for a risk neutral decision maker is determined using expected value (probability-weighted average); the branch probability is multiplied times the successor rollback value, and the products are summed.
  • 6. 162 Chapter 14 Introduction to Decision Trees • At a decision node, the rollback value is set equal to the highest rollback value on the immediate successor nodes. In TreePlan tree diagrams the rollback values are located to the left and below each decision, event, and terminal node. Terminal values and rollback values for the DriveTek problem are shown below. Figure 14.7 Terminal Node Rollback Values Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract 0.5 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0
  • 7. 14.4 Rollback Method 163 Figure 14.8 Electronic Event Node Rollback Value Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0 Figure 14.9 Magnetic Event Node Rollback Value Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $84,000 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0 At the event node following "Try electronic method," compute an expected value (probability- weighted average): = 0.5*150,000 + 0.5*30,000 = 75,000 + 15,000 = 90,000
  • 8. 164 Chapter 14 Introduction to Decision Trees At the event node following "Try magnetic method," compute an expected value: = 0.7*120,000 + 0.3*0 = 84,000 + 0 = 84,000 Figure 14.10 Method Decision Node Rollback Value Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $84,000 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0 At the decision node following "Awarded contract," choose the highest successor rollback value: = Max($80,000, $90,000, $84,000) = $90,000
  • 9. 14.4 Rollback Method 165 Figure 14.11 Contract Event Node Rollback Value Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $20,000 $84,000 0.3 Magnetic failure $0 0.5 Not awarded contract -$50,000 Don't prepare proposal $0 At the event node following "Prepare proposal," compute an expected value: = 0.5*90,000 + 0.5*(–50,000) = 45,000 + (–25,000) = 20,000 Figure 14.12 Proposal Decision Node Rollback Value Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $20,000 $84,000 0.3 Magnetic failure $0 0.5 $20,000 Not awarded contract -$50,000 Don't prepare proposal $0
  • 10. 166 Chapter 14 Introduction to Decision Trees At the initial decision node, choose the highest successor rollback value: = Max($20,000, $0) = $20,000 Figure 14.13 Rollback Optimal Choices Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $20,000 $84,000 0.3 Magnetic failure $0 0.5 $20,000 Not awarded contract -$50,000 Don't prepare proposal $0 At the initial decision node, choose "Prepare proposal." If "Awarded contract," choose "Try electronic method."
  • 11. 14.4 Rollback Method 167 Figure 14.14 Rollback Optimal Strategy Branches and Payoffs Use mechanical method $80,000 0.5 Electronic success 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 0.7 Magnetic success Prepare proposal Try magnetic method $120,000 $20,000 $84,000 0.3 Magnetic failure $0 0.5 $20,000 Not awarded contract -$50,000 Don't prepare proposal $0 Using the best choices at decision nodes (controllable) and depending on what happens at the event nodes (uncontrollable), there are three possible outcomes. Figure 14.15 All Rollback Values Use mechanical method $80,000 $80,000 0.5 Electronic success $150,000 0.5 Try electronic method $150,000 Awarded contract $90,000 0.5 $90,000 Electronic failure $30,000 $30,000 0.7 Magnetic success Prepare proposal $120,000 Try magnetic method $120,000 $20,000 $84,000 0.3 Magnetic failure $0 $0 0.5 $20,000 Not awarded contract -$50,000 -$50,000 Don't prepare proposal $0 $0
  • 12. 168 Chapter 14 Introduction to Decision Trees Optimal Strategy After the rollback method has determined certain equivalents for each node, the optimal strategy can be identified by working forward through the tree. At the initial decision node, the $20,000 rollback value equals the rollback value of the "Prepare proposal" branch, indicating the alternative that should be chosen. DriveTek will either be awarded the contract or not; there is a subsequent decision only if DriveTek obtains the contract. (In a more complicated decision tree, the optimal strategy must include decision choices for all decision nodes that might be encountered.) At the decision node following "Awarded contract," the $90,000 rollback value equals the rollback value of the "Try electronic method" branch, indicating the alternative that should be chosen. Subsequently, if the electronic method fails, DriveTek must use the mechanical method to satisfy the contract. 14.5 NEWOX DECISION TREE PROBLEM The Newox Company is considering whether or not to drill for natural gas on its own land. If they drill, their initial expenditure will be $40,000 for drilling costs. If they strike gas, they must spend an additional $30,000 to cap the well and provide the necessary hardware and control equipment. (This $30,000 cost is not a decision; it is associated with the event "strike gas.") If they decide to drill but no gas is found, there are no other subsequent alternatives, so their outcome value is $-40,000. If they drill and find gas, there are two alternatives. Newox could sell to West Gas, which has made a standing offer of $200,000 to purchase all rights to the gas well's production (assuming that Newox has actually found gas). Alternatively, if gas is found, Newox can decide to keep the well instead of selling to West Gas; in this case Newox manages the gas production and takes its chances by selling the gas on the open market. At the current price of natural gas, if gas is found it would have a value of $150,000 on the open market. However, there is a possibility that the price of gas will rise to double its current value, in which case a successful well will be worth $300,000. The company's engineers feel that the chance of finding gas is 30 percent; their staff economist thinks there is a 60 percent chance that the price of gas will double.