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Reactive Learning Agents

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Jeff Smith
Jeff Smith

Presented at the Google Developer Group NYC Meetup on 9/12/16 http://www.meetup.com/gdgnyc/events/231371634/ This talk is focused on the design of learning agents using the techniques of reactive machine learning. We explored the difference between software agents (bots), intelligent agents, and learning agents. As the most complex class of agent, a learning agent has a sophisticated internal architecture, which we broke down into different capabilities. Finally, we examined how the techniques from reactive machine learning can allow us to build learning capabilities into our agents. This talk is not just be about AI concepts, though. It covers a range of pragmatic techniques to aid you in your efforts to implement learning agents. Throughout, we considered where and how we can use external resources like libraries, services, datasets, and even humans to solve sub-problems in the agent design process.

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Reactive Learning Agents Jeff Smith @jeffksmithjr
Bio
Bio
Bio
x.ai @xdotai hello@human.x.ai New York, New York
Designing Agents
Agents
Software Agents
Software Agents Mmmm… Lunch.
Software Agents Sensors Actuators Function
Intelligent Agents
Intelligent Agents Maybe Later
Intelligent Agents Sensors Actuators Knowledge Function
Learning Agents
Learning Agents Not that One!
Learning Agents Sensors Actuators Knowledge Learning Function
Reactive Machine Learning
Reactive
Reactive Systems Responsive Resilient Elastic Message-Driven
Reactive Strategies Replication Containment Supervision
Reactive Machine Learning
Reactive Machine Learning Uncertain DataInfinite Data Laziness Pure Functions Immutable Facts Possible Worlds
Reactive Learning Agents
Learning Agents Sensors Actuators Knowledge Learning Function
Reactive Systems Responsive Resilient Elastic Message-Driven
Reactive
+ Learning AgentsReactive
Source of AI Components
Source of AI Components Yours
Source of AI Components Other People’s Yours
Sensors
Sensors •Email •Messaging Platforms •Phone cameras & sensors •Wearables
Sensors •Email •Messaging Platforms •Phone cameras & sensors •Wearables •Your Data Collection Systems
Reactive Data Collection
Reactive Data Collection
Reactive Data Collection
Reactive Data Collection
Reactive Data Collection
Reactive Data Collection
Reactive Data Collection •Replication via Distributed databases •Event-sourcing/immutable fact databases •Uncertainty-aware data models •AP Databases https://skillsmatter.com/skillscasts/7038-lightning-talks-2
Actuators
Actuators •Messaging platforms •Email •Notifications •External API Calls
Actuators •Messaging platforms •Email •Notifications •External API Calls •Robots •Self-driving Cars •Internal API Calls
Reactive Action Sensors Actuators Knowledge Learning Function
Reactive Action Sensors Actuators Knowledge Learning Function
Reactive Action Sensors Actuators Knowledge Learning Function
Reactive Action Sensors Actuators Knowledge Learning Function
Knowledge
Knowledge •External Datasets •Knowledge as a Service APIs
Knowledge •External Datasets •Knowledge as a Service APIs •Your Training corpus •Institutional knowledge
Elixir •Functional Language •Homoiconic Syntax •Concurrency-oriented •Runs on the bEAM (EVM)
User Data user2user1 user3
Reactive Knowledge Systems Adapted from https://github.com/mitchellhenke/circuit_breaker
Reactive Knowledge Systems
Reactive Knowledge Systems
Reactive Knowledge Systems
Reactive Knowledge Systems
Reactive Knowledge Systems
Learning
Learning •Machine Learning as a Service APIs •Open Source Libraries
Learning •Machine Learning as a Service APIs •Open Source Libraries •Your novel Algorithms •Organizational Learning
Reactive Learning
Reactive Learning
Reactive Learning Raw Data Features Model
Reactive Learning Raw Data Features Model
Reactive Learning Raw Data Features Model Raw Data Features Model
Reactive Learning Raw Data Features Model Raw Data Features Model
Reactive Learning Raw Data Features Model Raw Data Features Model
Reactive Learning Raw Data Features Model
Reactive Learning Raw Data Features Model https://youtu.be/B7XYlBaxglU
Agent Function
Agent Function •???
Agent Function •??? •Your Whole system
Reactive Agent Functions
Reactive Agent Functions
Reactive Agent Functions
Reactive Agent Functions
Reactive Agent Functions
Reactive Agent Functions
Reactive Agent Functions
Dialyzer in Action ml_system.ex:3: Function predict/1 has no local return ml_system.ex:6: The call 'Elixir.MLSystem':call_model_b(feature@1::number()) will never return since it differs in the 1st argument from the success typing arguments: (binary()) ml_system.ex:22: Invalid type specification for function 'Elixir.MLSystem':call_model_b/1. The success typing is (binary()) -> binary() ml_system.ex:23: Function call_model_b/1 has no local return
Dialyzer in Action ml_system.ex:24: The call 'Elixir.String':upcase(feature@1::number()) will never return since the success typing is (binary()) -> bitstring() and the contract is (t()) -> t() ml_system.ex:38: Function ensemble/1 will never be called
Testing Agent Functions Tool Tests Dialyzer Types QuickCheck Properties Concuerror Interleavings
Summary
Learning Agents Sensors Actuators Knowledge Learning Function
Reactive Systems Responsive Resilient Elastic Message-Driven
Reactive Machine Learning Uncertain DataInfinite Data Laziness Pure Functions Immutable Facts Possible Worlds
+ Learning AgentsReactive
Reactive Machine Learning reactivemachinelearning.com @jeffksmithjr Use the code gdgnycmu for 39% off the book!
x.ai @xdotai hello@human.x.ai New York, New York
x.ai @xdotai hello@human.x.ai New York, New York We’re hiring!
Thanks!
Reactive Learning Agents Jeff Smith @jeffksmithjr

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