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Introduction to Software Agent Technologies

Introduction to Software Agent Technologies. Von-Wun Soo, Professor Department of Computer Science. Outline. Introduction Agent fundamental theories Agent Architectures Agent Language Agent Building tools Applications.

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Introduction to Software Agent Technologies

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  1. Introduction to Software Agent Technologies Von-Wun Soo, Professor Department of Computer Science Von-Wun Soo 2000

  2. Outline • Introduction • Agent fundamental theories • Agent Architectures • Agent Language • Agent Building tools • Applications Von-Wun Soo 2000

  3. information explosion and overload due to the popularity of internet technology information supply (providers) information demand (consumers) personal assistance of information access and utilization enhance efficiency of communication and interaction among people construction of virtual agent-based communities and societies Why do we need the intelligent agent technology? Von-Wun Soo 2000

  4. Characteristics of Intelligent Agents • Autonomous, Proactive, and Rational: Intelligent agents have their own goals, and execute their tasks that optimize certain performance measures • Interactive/communicative: Interacting with environment and other agents Von-Wun Soo 2000

  5. What’s new in software agent technology? • A paradigm shift of information utilization from direct manipulation to indirect access and delegation • A kind of middleware between information demand (client) and information supply (server) • A software that has autonomous, personalized, adaptive, mobile, communicative, social abilities Von-Wun Soo 2000

  6. What intelligent agents can do? – Just a few examples • internet data gathering and retrieval • electronic news and mail filtering • calendar management and meeting scheduling • work-flow assistants • making travel arrangement • event monitoring • alerting users to investment opportunities • alerting doctors on emergency events of patients Von-Wun Soo 2000

  7. electronic commerce Buyer, sellers, brokers, banks virtual enterprise managers, manufacturers engineers, accountants digital library librarians, users virtual school teachers, students, classmates, staff virtual hospital physicians, staff, patients electronic government policy makers, officers, policemen, citizens Potential applications on virtual human societies Von-Wun Soo 2000

  8. Impacts of the software agents on information services • Information services become interactive and personalized • The service providers can record and induce from the user’s behaviors • The service provider can easily customize its services to different customers with low cost. Von-Wun Soo 2000

  9. Impacts of software agents on economy • Easy comparison of prices and access independent evaluations of products. • Double roles in market place: a buyer and a seller (e.g., e-auction) • A small company has potentials to become a global enterprise • Facilitates supply chain and manufacturing process management– Just-in-time delivery • Facilitates global reuse of corporate knowledge (knowledge management) Von-Wun Soo 2000

  10. Impacts of Software Agents on Information Service • Enhance the quality • Reduce the cost of information services. • Provide integrated services – knowledge and information sharing and reuse Von-Wun Soo 2000

  11. classify by mobility: stationary mobile classify by architecture: deliberative reactive social classify by attributes: collaborative agents interface agents learning agents classify by roles: match maker information gathering tutorial agents, etc Classification of intelligent agents Von-Wun Soo 2000

  12. Characteristics of software agents • Proactive: goal-oriented • Autonomy: bounded rationality • Social: communication, cooperation, team/coalition formation • Adaptive: learning from environment and other agents • Mobility: interoperability,navigation, persistent Von-Wun Soo 2000

  13. Environment of Agents • Accessible vs Inaccessible (chess vs taxi driving) • Fully observable vs partial observable (chess vs taxi driving) (image analysis vs part picking robot) • Deterministic vs Nondeterministic (stocahstic) • Episodic vs Nonepisodic (sequential) • (image analysis vs taxi drving) • Static vs Dynamic (chess vs taxi driving) • Discrete vs Continuous Von-Wun Soo 2000

  14. knowledge representation and inference planning machine learning/data mining & discovery common sense reasoning uncertainty reasoning distributed (multiple agents) problem solving constraint satisfaction intelligent man/machine interface user modeling How AI techniques used in the IA domains? Von-Wun Soo 2000

  15. Comparison between expert systems and intelligent agents • Expert systems address less communication and coordination issues • Expert systems tend to knowledge-driven and address less inferring joint intention and team behaviors • Address nothing about mobility • Autonomous agents vs consultant Von-Wun Soo 2000

  16. Comparison between objects and agents Von-Wun Soo 2000

  17. Outlines • Introduction • Agent fundamental theories • Agent Architectures • Agent Language • Agent Building tools • Applications Von-Wun Soo 2000

  18. Knowledge representation Problem solving and decision making Learning Cognitive states and emotion Multi-agent communication, coordination and negotiation Mobility Delegation and trust Security and privacy Mechanism design and agent platform Social reasoning Agent fundamental theories Von-Wun Soo 2000

  19. Agent knowledge representation • Data structure: databases, lists, queues, trees, graphs • Knowledge structure: rules, first order logics and modal logics, frames, scripts, semantic/belief networks, etc. • World/Environmental models • Models of other agents: who, where, capabilities Von-Wun Soo 2000

  20. representing and maintaining belief desire intention goal plan commitment convention representing and maintaining group belief; etc reasoning about other agents beliefs, etc influencing the intentions and beliefs of other agents Agent knowledge representation Von-Wun Soo 2000

  21. Modal logics Next , eventually , always , until  Possible world semantics Belief-goal compatibility Goal(a)  Bel(a) Goal-intension compatibility Intend(a) Goal(a) Intend(a) Bel(Intend(a)) Goal(a) Bel(Goal(a)) Intend(a) Goal(Intend(a))) Belief Desire Intention BDIMike Georgeff Von-Wun Soo 2000

  22. BDI • rationality • Belief + desire => intention Desire => goal Intention => plan • Commitment is stronger than desire and intention Von-Wun Soo 2000

  23. Blind commitment Intend(inevitable )  inevitable(Intend(inevitable )  Bel()) Single-minded commitment Intend(inevitable )  inevitable(Intend(inevitable )  (Bel()Bel(optional ) ) Open-minded commitment Intend(inevitable )  Inevitable(Intend(inevitable )  (Bel() Goal(optional ))) Commitments as axioms of change Von-Wun Soo 2000

  24. Social Commitment [Castelfranchi] • Individual commitment, collective commitment, Social commitment • Individual vs Collective commitment • Social commitments capture the obligations from one party to another • Executive commitment vs. high-level commitment • Task/action commitment • Goal commitment • Value commitment Von-Wun Soo 2000

  25. Agent Problem Solving and Decision Making • Logical inference • Rule-based inference • Constraint satisfaction • Planning • Decision theoretical reasoning (rationality) • Learning (inductive reasoning, reinforcement learning, etc.) • Conceptual formation (unsupervised learning and world modeling, etc) Von-Wun Soo 2000

  26. Agent Learning • Personalization/user profile • Performance improvement/adaptation • Learning environment • Learning other agents • Learning to communicate and negotiation Von-Wun Soo 2000

  27. Agent learning techniques • Reinforcement learning Given rewards at different situations, select optimal action based on acquired action policy functions • Supervised learning Given (positive and negative) classifications on training examples wrt the target concepts provided by a teacher, generate classification functions on the classes • Unsupervised learning Given training examples, clustering or forming concepts based on similarities and discrepancies among training examples • Bayesian learning • etc. Von-Wun Soo 2000

  28. Delegation and trust • Task assignments Optimal delegation tasks based on global profit gain and individual gains • Transfer of authority and rights How legal issues such as extent of permission and obligation right can be transferred • Trust, deception and risk issues Modeling and representation of what extent can an agent be trusted, to avoid being deceived, decision making of how an action can incur risk or loss • Security and privacy System implementations to ensure agents to conduct in a safe and comfortable environment Von-Wun Soo 2000

  29. Multi-agent coordination • Cooperation, collaboration and competition • Joint goal/intention • Joint plan • Team behaviors • Coalition formation Von-Wun Soo 2000

  30. Multi-agent Communication • Speech Act theory: (illocutionary act, perlocutionary act) • illocutionary act: • the utterance of words (utterance acts) • making reference and predicating (propositional acts) a particular intention in making the utterance (illocutionary force) • Perlocutionary act: • the production of a particular effect in the addressee Von-Wun Soo 2000

  31. Performatives • A Performative is a speech act • Promise, assert, request, confirm, ask, reject, …. • KQML agent communication language (ACL) Von-Wun Soo 2000

  32. Von-Wun Soo 2000

  33. Multi-agent communication • Natural language generation (HMI) • Natural language recognition (HMI) • Dialogue & discourse analysis • Communication Protocol design and analysis Von-Wun Soo 2000

  34. Why multi-agent coordination is important? • human complex problem solving are multi-agent in nature -- distributed problem solving and distributed artificial intelligence • resolve conflicts among multi-agents • prevent an anarchy or chaos (everyone listen to only one agent; no agents listen to any agent) • satisfy global constraints and by working as a team, enhance global welfare or performance • sharing information, synchronizing actions, avoid redundancy Von-Wun Soo 2000

  35. Techniques of Coordination • Centralized vs distributed • Compiled convention of social laws • Knowledge-transfer protocol -- blackboard • Organization-structure • Contracting (Contract net protocol) • Inferring other agents via observation– focal points • Negotiation approaches Von-Wun Soo 2000

  36. Game-theoretic Approaches • Study of conflict analysis among agents • Seek equilibrium (stable state) solutions • Explanation of behaviors and decision making among multiple agents under various game-theoretic assumptions • A Prisoner’s Dilemma game Von-Wun Soo 2000

  37. A prisoner’s dilemma game Q Q P Cooperate Fink P Cooperate Fink - 1 - 1.1 - 1 0 Cooperate - 1 - 10 Cooperate - 1 - 10 - 10 - 9.1 - 10 - 8 Fink - 1.1 - 9.1 Fink 0 - 8 (a) (b) Prisoner's Dilemma game matrix (a) A special case of a PD game matrix. (b) A dilemma-free game matrix. Note: (-1,-1) Pareto-dominate all three other strategy combinations Von-Wun Soo 2000

  38. Economic Models • Market mechanisms: auction Allocate good items to suitable agents • Different types of auctions: Rules of auctions • Open cry vs Sealed bid, • Increasing vs decreasing bidding • Winner at first price or second price, etc. • dropout (leaving the auction and cannot return) • One-sided, two sided (double) • One shot, repeated • English auction, (first price, open cry, increasing) • Dutch auction, (first price, open cry, decreasing) • Vickrey auction, (Second price, open cry, increasing) • Japanese auction ( Like English auction, except with dropout) Von-Wun Soo 2000

  39. Artificial Life • Mimic behaviors of natural lifes either individually or collectively • For lower species of animals or plants, simulate their responses to outside stimulus and internal physiological change, etc • It could be modeled up to the genetic levels • It could be applied to model individual, groups or even a whole ecology. Von-Wun Soo 2000

  40. Mobile Agents • Why we have to design mobile agents? • Necessity of mobile agents: • Tradeoffs between the data and decision making: • Advantages vs Disadvantages Von-Wun Soo 2000

  41. Mobile Agents • Navigation of mobile agents • Transportation and persistency of agents • Naming and paging of mobile agents • Interoperability of mobile agents • Mobile agent platforms– provide mobile object environment • IBM Aglet • Voyager Von-Wun Soo 2000

  42. Scenarios for applications of mobile agents • Mobile Agent Assistants for personal traveling • Personal purchasing mobile agents Von-Wun Soo 2000

  43. Outline • Introduction • Agent fundamental theories • Agent Architectures • Agent Language • Agent Building tools • Applications Von-Wun Soo 2000

  44. Desiderata of Agent Architecture • Support effective reactive, deliberative, proactive and social responses of agents to outside stimuli (from either environmental or other agents) • Support multi-agent coordination and interactions • Support learning and adaptive from previous behaviors and performance feedback Von-Wun Soo 2000

  45. Agent Architectures • Single agent architecture: • Layered: Vertical vs horizontal • Reactive vs deliberative vs proactive vs social • Multi-agent architecture: • Brokerage vs match-maker • Yellow-page vs white-page Von-Wun Soo 2000

  46. Single agent vs multi-agents • Single agent architecture • function roles in internal modules or layers • Multi-agent architecture • Functional roles as mediation such as broker, facilitator, match maker, proxy agents • Social agents • Different social roles of agents • Organization and enterprise • Market agents • Buyer and seller, auctioneer and trusted third party Von-Wun Soo 2000

  47. Single Agent architecture • possible layers of agents: • perception and action • reactivity (behavior-based layer) • local planning • cooperation • modeling • intention • learning Von-Wun Soo 2000

  48. actions perception Vertical and Horizontal Subsumption architecture, Touring Machines perception actions perception actions InteRRaP and MECCA Von-Wun Soo 2000

  49. TouringMachines Modeling layer Planning layer Action Subsystem Perception subsystem Reactive layer Control Subsystem Von-Wun Soo 2000

  50. The InteRRap hybrid architecture [Mueller] Von-Wun Soo 2000

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