This document provides an introduction to mechanism design theory and its applications. It discusses how mechanism design can be used to implement desired social outcomes even when individuals act in their own self-interest. Examples are provided, such as dividing a cake fairly or choosing an optimal public energy source. The document also discusses how algorithmic mechanism design incorporates computer science concepts to solve distributed problems with self-interested agents. Truthful mechanisms like Vickrey-Clarke-Groves are described as an important class of mechanisms. In summary, the document introduces key concepts in mechanism design theory and its uses in algorithmic settings to achieve social goals.
Lecture slides on Mechanism Design, which are entirely based on the following well-known survey article.
Jackson, M. O. (2014). Mechanism theory.
http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2542983
The below is a link to my corse website:
https://sites.google.com/site/yosukeyasuda2/home/lecture/optimization15
Lecture slides on Mechanism Design, which are entirely based on the following well-known survey article.
Jackson, M. O. (2014). Mechanism theory.
http://papers.ssrn.com/sol3/Papers.cfm?abstract_id=2542983
The below is a link to my corse website:
https://sites.google.com/site/yosukeyasuda2/home/lecture/optimization15
Static force analysis, Unit-1 of Dynamics of machines of VTU Syllabus compiled by Hareesha N Gowda, Asst. Prof, Dayananda Sagar College of Engg, Blore. Please write to hareeshang@gmail.com for suggestions and criticisms.
In modern developing world, automatic
plays important role especially two-wheeler i.e., (motorcycle
and bikes) plays a major role .Even though they are helpful
there are some sad events like accidents due to careless of
rider. Major accidents occur due to forgetting of lifting side
stand. To rectify this problem many advance measure have
taken, but they are useless, so as a by considering that it should
be implemented practically in all types bikes the new system
“SPROCKET SIDE STAND RETRIEVE SYSTEM” this
system can be attached in all type of two-wheeler (mopeds,
geared, non-geared, hand geared bikes) and it is designed
based on the working principal of bikes.
BEST PPT FOR DOWNLOADING & SUBMISSION
INFORMATION IN POINTS
When the inertia forces are considered in the analysis of the mechanism, the analysis is known as dynamic force analysis.
Now applying D’Alembert principle one may reduce a dynamic system into an equivalent static system and use the techniques used in static force analysis to study the system.
Garcia and Bayo (1994), Wang and Wang (1998), Shi and Mc Phee (2000) were interested in the analytical and
experimental study of the dynamic response of these mechanisms
Static force analysis, Unit-1 of Dynamics of machines of VTU Syllabus compiled by Hareesha N Gowda, Asst. Prof, Dayananda Sagar College of Engg, Blore. Please write to hareeshang@gmail.com for suggestions and criticisms.
In modern developing world, automatic
plays important role especially two-wheeler i.e., (motorcycle
and bikes) plays a major role .Even though they are helpful
there are some sad events like accidents due to careless of
rider. Major accidents occur due to forgetting of lifting side
stand. To rectify this problem many advance measure have
taken, but they are useless, so as a by considering that it should
be implemented practically in all types bikes the new system
“SPROCKET SIDE STAND RETRIEVE SYSTEM” this
system can be attached in all type of two-wheeler (mopeds,
geared, non-geared, hand geared bikes) and it is designed
based on the working principal of bikes.
BEST PPT FOR DOWNLOADING & SUBMISSION
INFORMATION IN POINTS
When the inertia forces are considered in the analysis of the mechanism, the analysis is known as dynamic force analysis.
Now applying D’Alembert principle one may reduce a dynamic system into an equivalent static system and use the techniques used in static force analysis to study the system.
Garcia and Bayo (1994), Wang and Wang (1998), Shi and Mc Phee (2000) were interested in the analytical and
experimental study of the dynamic response of these mechanisms
-What goods should or should not be publicly provided -What effSilvaGraf83
-What goods should or should not be publicly provided?
-What effect does changing the regulatory environment change economic activity?
-How should we go about collecting revenue?
-Does changing any of these things effect overall welfare, both individually and socially? How so?
-What are the tradeoffs?
-We're trying to assess what government should do.
-Positive analysis=What is?
-Normative analysis=What ought to be/should be?
-Tradeoff between equity (i.e. fariness) and economic efficiency (MB>=MC)
-Excess burden (in public finance) and deadweight loss (in economics)
-Impose high taxes on more relatively inelastic goods to generate revenue (lack of substitutes, think about gas)
-Ramsey Rule (will end up with a fairly efficient tax, not necessarily equitable)
-Equality and efficiency are generally opposed to each other
-Broad questions
1.) Is it possible to draw normative conclusions from positive analysis?
2.) Can we evaluate normative conclusions and try to predict outcomes through positive analysis?
3.) How can we go about measuring the expected or actual impact of a policy proposal?
4.) How do these issues impact individual or societal welfare (can we measure them and what is societal welfare)?
5.) What is the difference between blackboard economics and real world policy?
-We need to have a way to analyze the effects of policy on overall welfare
-At least in the US, all regulatory agencies are required to conduct cost-benefit analysis before implementing a regulation; needs to conclude whether or not to impose the regulation
-Obviously, if no policy can survive cost-benefit analysis, then you're in a Pareto Optimal situation; if it can, then it is at least Kaldor-Hicks efficient
-We are not measuring goodness or badness
-What we are trying to do is evaluate whether a policy will be worth the costs; we're going to get at this through social welfare
-Marginal cost is less than or equal to marginal benefit (stop at MC=MB)
-Example: Cutting off your head for stealing from grandma; people will only steal when no one else is around, hence the only witness is grandma; the criminal is incentivized to murder grandma as well
-Optimal level of crime is greater than 0
-Caveats with Cost-Benefit Analysis
1.) CBA is not about money.
2.) Not about inputs and outputs.
3.) CBA is about welfare.
4.) Requires a common denominator in order to express heterogeneous items into homogenous flows. This is where money comes into CBA. It allows us to compare these different measures that we have.
-We need to think in terms of outputs and the effects that these outputs have on welfare. These are going to become a means to increase welfare.
-Utlimately, we need to think terms of the social value that is achieved through the outputs that we obtain relative to the opportunity costs of the project.
-Minor League Baseball Stadium Example: Troy evaluates the success of the stadium based on attendance. Could just set the ticket price ...
-What goods should or should not be publicly provided -What effMartineMccracken314
-What goods should or should not be publicly provided?
-What effect does changing the regulatory environment change economic activity?
-How should we go about collecting revenue?
-Does changing any of these things effect overall welfare, both individually and socially? How so?
-What are the tradeoffs?
-We're trying to assess what government should do.
-Positive analysis=What is?
-Normative analysis=What ought to be/should be?
-Tradeoff between equity (i.e. fariness) and economic efficiency (MB>=MC)
-Excess burden (in public finance) and deadweight loss (in economics)
-Impose high taxes on more relatively inelastic goods to generate revenue (lack of substitutes, think about gas)
-Ramsey Rule (will end up with a fairly efficient tax, not necessarily equitable)
-Equality and efficiency are generally opposed to each other
-Broad questions
1.) Is it possible to draw normative conclusions from positive analysis?
2.) Can we evaluate normative conclusions and try to predict outcomes through positive analysis?
3.) How can we go about measuring the expected or actual impact of a policy proposal?
4.) How do these issues impact individual or societal welfare (can we measure them and what is societal welfare)?
5.) What is the difference between blackboard economics and real world policy?
-We need to have a way to analyze the effects of policy on overall welfare
-At least in the US, all regulatory agencies are required to conduct cost-benefit analysis before implementing a regulation; needs to conclude whether or not to impose the regulation
-Obviously, if no policy can survive cost-benefit analysis, then you're in a Pareto Optimal situation; if it can, then it is at least Kaldor-Hicks efficient
-We are not measuring goodness or badness
-What we are trying to do is evaluate whether a policy will be worth the costs; we're going to get at this through social welfare
-Marginal cost is less than or equal to marginal benefit (stop at MC=MB)
-Example: Cutting off your head for stealing from grandma; people will only steal when no one else is around, hence the only witness is grandma; the criminal is incentivized to murder grandma as well
-Optimal level of crime is greater than 0
-Caveats with Cost-Benefit Analysis
1.) CBA is not about money.
2.) Not about inputs and outputs.
3.) CBA is about welfare.
4.) Requires a common denominator in order to express heterogeneous items into homogenous flows. This is where money comes into CBA. It allows us to compare these different measures that we have.
-We need to think in terms of outputs and the effects that these outputs have on welfare. These are going to become a means to increase welfare.
-Utlimately, we need to think terms of the social value that is achieved through the outputs that we obtain relative to the opportunity costs of the project.
-Minor League Baseball Stadium Example: Troy evaluates the success of the stadium based on attendance. Could just set the ticket price ...
A presentation at the Open University, Milton Keynes, 2003. The paper presents three different examples of simulation: An agent-based model of adaptive behaviour in oligopoly, a learning model of consumption and lifestyle and a preliminary attempt to model social mobility processes.
Future of AI-powered automation in businessLouis Dorard
Starting from examples of current use cases of AI in business and in everyday life, we'll see what the future holds and we'll mention questions to address when giving autonomy to intelligent machines. We'll also aim at demystifying how AI works, in particular how machines can use data to automatically learn business rules and actions to perform in different contexts.
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It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
1400 to 2000 words Ethical Theories to Apply Utilitarianism, Univ.docxLyndonPelletier761
1400 to 2000 words
Ethical Theories to Apply: Utilitarianism, Universal Ethics, Golden Rule, Virtue Ethics
You work in the Ethics Department for ABC Company (ABC). Your department is dedicated to advising its employees about their ethical obligations in the corporate setting. You are an internal consultant who provides advice and most importantly, recommendations for action to employees of the firm. All communications you receive in this capacity are confidential.
Luke, an employee of ABC, comes to you with the following scenario and asks for your advice. He wants to fully consider the situation. Your task is to advise and recommend a course of action based on the specified ethical lenses and facts as given. Below are the facts that Luke provides to you.
*****
Luke has been asked to work on a project that involves developing land recently purchased by ABC to build an adult entertainment retail store. According to the plan, the land is located on the corner of the neighborhood where Owen, Luke’s brother, lives.
Luke knows that as soon as the plans for the store are made public, property values for the surrounding neighborhood will decrease significantly. ABC plans to publicly announce the project one month from today.
Luke is concerned about his obligations of confidentiality to his company. However, Luke is also very close to Owen, who recently told Luke that he received an offer to sell his house at an “okay” price given the current real estate market. Owen is considering selling but hasn’t made any final decision yet. He wonders if he might get a better offer a few years from now when the real estate market improves.
What is the ethical issue, why is this an issue, and what should Luke do about it?
*****
For assignment 4,
prepare a memo,
setting out your analysis
and
recommendations,
that considers ONLY the
following ethical lenses: Utilitarianism, Universal Ethics (i.e., Kant’s categorical imperative), The Golden Rule and Virtue Ethics.
Remember: follow all instructions, NO MISSING ANYTHING
Utilitarianism:
1)
argument need to be developed more clearly to consider all consequences on all affected stakeholder
2)
consider all implications of each action on all stakeholders, considering all the benefit and harms. What are all the consequences (societal harms and benefits) if luke divulges the information? What would be consequences (societal harm and benefits) of not divulging the news?
3)
Show clearly which one of the choices results in greater good for greater numbers
4)
What are the criticism of the theory. How could they influence Luke’s decision here?
5)
What Luke must do as per this theory?
Universal Ethics:
1.
Defined Rule (used your own words)
2.
Tell the rule how work in this case
3.
While applying the theory, should have discussed what kind of a world it would be if all employees shares information with their relatives/friends at the expense of their companies
4.
How would it affect business environment?
.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
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See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
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• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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https://arxiv.org/abs/2306.08302
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1. Mechanism Design Theory:
How to Implement Social Goals
Examples and Algorithmic Design
Stathis Grigoropoulos
Ioannis Katsikarelis
Multi-Agent Systems Utrecht University 2012
3. Introduction
Game Theory : A Normal Game Form[1]
– A Set of Players: Who is involved?
– A Set of Rules (Institutions): What can the players do?
– A Set of Outcomes: What will happen when players perform a certain
action?
– A Set of Preferences: What players want the most of the possible outcomes?
The importance of Game Theory is established in numerous fields:
– Economic Phenomena
– Auctions, Bargains, Fair Division
– Social Phenomena
– Social Network Formation, Social Choice
– Political Sciences
– Election outcome, Political choices
4. Introduction
A closer look at a “real” case[2]:
• You are selling a rare painting for which you want to raise the
maximum revenue.
– Tyler, who values the painting at $100,000
– Alex who values it at $20,000
• You do not know their valuation, how to get max revenue?
– Auction!
– If you knew, you would set the price at $99,999 and be fine!
• Standard English open-cry Auction $20,001 (not max!)
• + Reserve Price say at $50,000 $50,001 (close, but..lucky!)
• But why stop at a reserve price? How about a reserve price
and an entry fee? But why stop at reserve prices and entry
fees?....
5. Context
The design of the institutions (Rules) through which individuals
(Players) interact can have a profound impact on the results
(Outcomes) of that interaction[3].
We saw:
• Auction is conducted with sealed bids versus oral ascending bids can have
an impact on what bidders learn about each other's valuations and
ultimately how they bid.
• Wanted: forecast the economic or social outcomes that these
institutions generate
6. Context
Theory of Mechanism Design[4]
“engineering” part of economic theory
• much of economic theory devoted to:
– understanding existing economic institutions
– explaining/predicting outcomes that institutions generate
– positive, predictive
• mechanism design – reverses the direction
– begins by identifying desired outcomes (goals)
– asks whether institutions (mechanisms) could be designed to achieve
goals
– if so, what forms would institutions take?
– normative, prescriptive - - i.e., part of welfare economics
7. Examples
Simple example[5], suppose
• mother wants to divide cake between 2 children, Alice and
Bob
• goal: divide so that each child is happy with his/her portion
– Bob thinks he has got at least half
– Alice thinks she has got at least half
call this fair division
• If mother knows that the kids see the cake in same way she
does, simple solution:
– she divides equally (in her view)
– gives each kid a portion
8. Examples
• But what if, say, Bob sees cake differently from
mother?
– she thinks she’s divided it equally
– but he thinks piece he’s received is smaller than Alice’s
• difficulty: mother wants to achieve fair division
– but does not have enough information to do this on her own
– in effect, does not know which division is fair
9. Examples
• Can she design a mechanism (procedure) for which
outcome will be a fair division?
(even though she does not know what is fair herself ?)
• Age-old problem
– Lot and Abraham dividing grazing land
10. Examples
Age-old solution:
– have Bob divide the cake in two
– have Alice choose one of the pieces
Why does this work?
• Bob will divide so that pieces are equal in his eyes
– if one of the pieces were bigger, then Alice would take that one
• So whichever piece Alice takes, Bob will be happy with other
• And Alice will be happy with her own choice because if she
thinks pieces unequal, can take bigger one
11. Examples
Example illustrates key features of mechanism design:
• mechanism designer herself doesn’t know in advance what
outcomes are optimal
• so must proceed indirectly through a mechanism
– have participants themselves generate information needed to identify
optimal outcome
• complication: participants don’t care about mechanism
designer’s goals
– have their own objectives
• so mechanism must be incentive compatible
– must reconcile social and individual goals
12. Examples
Example from the paper
Consider society with
• 2 consumers of energy – Alice and Bob
• Energy authority – must choose public energy source
gas
oil
nuclear power
coal
13. Examples
Two states of world
State 1 consumers weight future lightly (future relatively unimportant)
state 2 consumers weight future heavily (future relatively important)
Alice – cares mainly about convenience
In state 1: favors gas over oil, oil over coal, and coal over nuclear
In state 2: favors nuclear over gas, gas over coal, and coal over oil
− technical advances expected to make gas, coal, and
especially
nuclear easier to use in future compared with oil
Bob – cares more about safety
In state 1: favors nuclear over oil, oil over coal, and coal over gas
In state 2: favors oil over gas, gas over coal, and coal over nuclear
− disposal of nuclear waste will loom large
− gas will become safer
15. Examples
State 1
State 2
Alice
Bob
gas
nuclear
oil
oil
coal
coal
nuclear
gas
oil optimal
Alice
Bob
nuclear
oil
gas
gas
coal
coal
oil
nuclear
gas optimal
− authority could ask Alice or Bob about state
• but Alice has incentive to say “state 2” regardless of truth
always prefers gas to oil
gas optimal in state 2
• Bob always has incentive to say “state 1”
always prefers oil to gas
oil optimal state 1
So, simply asking consumers to reveal actual state too naive a mechanism
16. Examples
State 1
State 2
Alice
Bob
gas
nuclear
oil
oil
coal
coal
nuclear
gas
social optimum: oil
Alice
Bob
nuclear
oil
gas
gas
coal
coal
oil
nuclear
social optimum: gas
Authority can have consumers participate in the mechanism given by table
Bob
Alice
oil
coal
nuclear
gas
• Alice – can choose top row or bottom row
• Bob – can choose left column or right column
• outcomes given by table entries
• If state 1 holds
Alice will prefer top row if Bob plays left column
Bob will always prefer left column
so (Alice plays top, Bob plays left) is Nash equilibrium
neither participant has incentive to change unilaterally to another strategy
− so good prediction of what Alice and Bob will do
17. Examples
State 1
State 2
Alice
Bob
gas
nuclear
oil
oil
coal
coal
nuclear
gas
social optimum: oil
Alice
Bob
nuclear
oil
gas
gas
coal
coal
oil
nuclear
social optimum: gas
Bob
Alice
So, in state 1:
expect that
Alice will play top strategy
Bob will play left strategy
outcome is oil
oil is social optimum
Similarly, in state 2: gas is social optimum
oil
coal
nuclear
gas
18. Examples
State 1
State 2
Alice
Bob
gas
nuclear
oil
oil
coal
coal
nuclear
gas
social optimum: oil
Alice
Bob
nuclear
oil
gas
gas
coal
coal
oil
nuclear
social optimum: gas
Bob
Alice
oil
coal
nuclear
gas
• Thus, in either state, mechanism achieves social optimum, even though
− mechanism designer does not know the state herself
− Alice and Bob interested in own ends (not social goal)
• We say that mechanism implements the designer’s goals (oil in state 1,
gas in state 2)
19. Examples
State 1
State 2
Alice
Bob
gas
nuclear
oil
oil
coal
coal
nuclear
gas
optimum: oil
Alice
Bob
gas
nuclear
oil
oil
nuclear
coal
coal
gas
optimum: nuclear
Let us change the example a bit:
• Wrongly set nuclear as social optimum, observe that although oil is optimal
in state 1, it is not optimal in state 2, despite the fact that it falls in neither
Alice’s nor Bob’s rankings between states 1 and 2
• monotonicity is a property ensuring that the oil remain optimal in state 2
Theorem 1 (Maskin 1977): If a social choice rule is implementable, then it
must be monotonic.
Theorem 2 (Maskin 1977): Suppose that there are at least three individuals.
If the social choice rule satisfies monotonicity and no veto power, then it is
implementable.
20. Algorithmic Design
• Have shown you mechanisms in the cake, and
energy examples
• What about that auction?
• Examples raise questions (among others):
− How can we implement such a mechanism?
− How does Computer Science come into play?
21. Algorithmic Settings
●
●
●
●
An important part of Computer Science
research deals with distributed settings
These mainly focus on the connection of
several computers and the computations these
perform to achieve a common outcome
according to some protocol (algorithm)
It is generally assumed that the participants
follow the instructions of the protocol
This is obviously not always the case
(e.g. the Internet)
22. Two example applications
●
Load Balancing:
–
–
●
In a “perfect” world, the aggregate computational power of all
computers on the Internet would be optimally allocated online
among connected processors, which is in itself a difficult problem
In reality, all resources belong to individual entities that act in a
rationally selfish way, which implies the necessity of some form of
motivation for participation
Routing:
–
Information passes through several intermediate routers before
reaching its intended destination
–
Since routers are considered self-interested entities, this implies
that the protocols employed should take the router's potential
interests into consideration
23. Algorithmic Mechanism Design
●
●
●
●
Nisan and Ronen [6] used notions of mechanism
design to introduce a new framework for the
study of such problems
Theirs was not the first use of such notions in
Computer Science studies, but arguably one of the
most relevant and influential
This marriage of concepts has even more
interesting implications (e.g. complexity)
We only briefly mention the first steps of what is
now recognized as an important research direction
24. The model: Problems
●
Output specifications, defined algorithmically
–
–
●
Input is information about the setting (common) and the
participating agents (their types – private)
Output is the specific computed outcome, based on the
information above
Descriptions of agents' desires (preferences)
–
–
●
A valuation function for every agent, based on its type and
outcome
A payment from the mechanism to every agent for
participating, based on its type
The optimization version has an objective
function as an outcome
25. The model: Solutions
●
●
●
●
A problem is solved when the required output
is obtained, while agents try to achieve their
goals (maximize their utilities)
Agents have a specified family of strategies
and the outcome depends on all these choices
Depending on its strategy, the mechanism
provides a payment to each agent, which can
be used to make the agents' desires compatible
with the required outcome
Complexity matters
26. Desired characteristics of Mechanisms
●
Implementations with dominant strategies
–
–
●
Every agent has some dominant strategy
Every set of dominant strategies yields a desired outcome
Truthful Implementation
–
–
●
All agents want to report their type (no manipulation)
Correctly reporting one's type is a dominant strategy
The revelation principle states that given a
mechanism that implements a problem with
dominant strategies, there exists a truthful
implementation as well
27. Vickrey-Groves-Clarke Mechanisms
●
●
●
●
●
Originally defined for auctions (second-price)
VGC is a very useful type of mechanism,
applied to maximization problems, where the
objective is the sum of all agents' valuations
Intuitively, the payment defined by VGC for
an agent is its contribution to social welfare
VGC mechanisms have been famously proven
to be truthful (may even be the only truthful
implementations)
Complexity matters a lot
28. Shortest Paths Example
●
●
●
●
●
Consider a communication network, modeled
by a directed graph
There is one source and one sink node
Every edge is an agent, whose type (private
information) is te, the cost for sending a single
message across this edge
The goal is to find the cheapest path from the
source to the sink (single message)
Agent's valuation is 0 if its edge is not part of
e
the chosen path and -t otherwise
29. A Truthful Implementation
●
●
When all agents honestly report their types
(costs), the cheapest path can be calculated
The following mechanism ensures the above
is a dominant strategy for each agent:
Set the payment for each agent to be pe=0 if
its edge is not in the shortest path and
pe=dG-e-dG|e=0 otherwise (according to inputs)
●
●
This is a VGC mechanism, the computed
paths are the shortest paths and truth-telling is
a dominant strategy
Similar ideas are being used in today's Internet
30. Conclusion
•
Have seen some implemetations of the theory of
Mechanism Design
Many other potential applications
•
–
–
–
•
•
Policies to prevent financial crises
Sustainable gas emission policies
Elections Design
Combining Mechanism Design and Algorithmics is
very natural and yields interesting and useful
results
Although we merely mentioned a small part of
some introductory notions, the underlying theory is
itself plentiful and well-founded
32. References
1.
2.
3.
4.
5.
6.
Yoav Shoham, Kevin Leyton-Brown Multiagent Systems Algorithmic,
Game-Theoretic, and Logical Foundations, 2009
http://marginalrevolution.com/marginalrevolution/2007/10/mechanism-desig.html
, Mechanism Design for Grandma by Alex Tabarrok on October 15, 2007
Matthew O. Jackson, Mechanism Theory ,
https://www2.bc.edu/~unver/teaching/gradmicro/mechtheo.pdf revised
December 8 2003
Mechanism Design:How to Implement Social Goals (Eric S. Maskin)
Mechanism Design:How to Implement Social Goals , presentation by Eric S.
Maskin, Mechanism Design Theory(Harvard, Frankfurt, Shanghai, Prato,
Berlin).pdf, stifterverband.info/.../maskin_mechanism_design_theory.pdf,
visited 22-11-2012
Algorithmic Mechanism Design, Noam Nisan, Amir Ronen, Games and
Economic Behavior, Volume 35, Issues 1-2, April 2001, Pages 166-196