Agents

1. Agents Service-Oriented Computing: Semantics, Processes, Agents– Munindar P. Singh and Michael N. Huhns, Wiley, 2005

2. Highlights of this Section • Agents Introduced • Agent Environments • Agent Descriptions • Abstractions for Composition • Describing Compositions • Service Composition as Planning • Rules Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

3. What is an Agent? The term agent in computing covers a wide range of behavior and functionality • An agent is an active computational entity • With a persistent identity • Perceives, reasons about, and initiates activities in its environment • Communicates (with other agents) and changes its behavior based on others • Agents model business partners naturally and fit into open environments Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

4. Agents and MAS for SOC Relevance of agents for services? • Need for autonomy, heterogeneity, dynamism Unlike objects, agents • Are proactive and autonomous • Form commitments and communicate Moreover, agents can • Cooperate or compete • Model themselves, their users, and their competitors • Use and reconcile ontologies Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

5. Modeling Agents: AI Traditionally, emphasize mental concepts Beliefs: agent’s representation of the world Knowledge: (usually) true beliefs Desires: preferred states of the world Goals: consistent desires Intentions: goals adopted for action Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

6. Modeling Agents: MAS • Emphasize interaction • Social: about collections of agents • Organizational: about teams and groups • Ethical: about right and wrong actions • Legal: about contracts and compliance • Apply in all major applications • Support autonomy and communication, which are otherwise ignored Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

7. Agents versus AI Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

8. Mapping the Agent Abstractions Agents as components of an open system • Loose coupling => communication • Dynamism => autonomy • Openness and compliance => ability to enter into and obey contracts • Trustworthiness => ethical behavior Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

9. A Reactive Agent in an Environment Environment e; RuleSet r; while (true) { state = senseEnvironment(e); a = chooseAction(state, r); e.applyAction(a); } Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

10. Characteristics of Agent Environments • Observability: can aspects relevant to actions be sensed? • Determinism: is the history completely determined by the initial state and the agent’s actions? • History Freedom: does action choice depend on previous episodes or just the current episode? • Dynamism: can the environment change while agent is deliberating? • Continuity: do the agent actions, environment state variables, and time points have a continuous range of values? • Multiagent: is the agent aware of others that can affect the environment? Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

11. Agent Architectures, Abstractly • Set of environmental states, S={s1, s2, …} • Set of actions (of an agent), A = {a1, a2, …} • Agent: a decision function S*A, which maps a sequence of environment states to an action • Behavior (evolution) of an environment: a function, Env: S x A Powerset(S) • An agent’s interaction with its environment corresponds to a history h, whereh = (a0, s0 )  ( a1,s1 ) ( a2,s2 )…(au, su) (au+1,su+1 ) … Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

12. Agent Architectures • Logic-Based • Reactive • Belief-Desire-Intention (BDI) • Layered Architecture Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

13. Logic-Based Agents • An agent is a knowledge-based system • Contains an explicitly represented symbolic model of the world • Takes decisions via symbolic reasoning (logical deduction) • Problems: • Maintaining accurate adequate symbolic descriptions of the real world in real-time • Representing information symbolically about complex real-world entities Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

14. A Rational Agent Rationality depends on ... • A performance measure for success (e.g., expected utility) • What the agent has perceived so far • What the agent knows about the environment • The actions the agent can perform An ideal rational agent:for each possible percept sequence, it acts to maximize its expected utility, on the basis of its knowledge and the evidence from the percept sequence Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

15. Cognitive Architecture for an Agent Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

16. Reactive Architecture • Does not rely on symbol manipulation • Seeks to produce intelligent behavior without explicit • Symbolic representations • Abstract reasoning • Intelligence is an emergent property of certain complex systems • Cannot plan to drive a car to full detail • Reactively avoiding collisions while heading toward an attractor indicates intelligence Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

17. Subsumption Architecture A kind of reactive architecture • A hierarchy of task-accomplishing behaviors • Each behavior is a rather simple rule-like structure • Each behavior competes with others to exercise control over the agent • Lower layers present more primitive kinds of behavior • In terms of computation, the resulting systems are extremely simple Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

18. BDI • Deciding on what goals to achieve and how to achieve them • Beliefs: the information an agent has about its surroundings • Desires: the things that an agent would like to see achieved • Intentions: the desires that an agent is working on; also involves a deeper personal commitment • A BDI architecture addresses how beliefs, desires and intentions are represented, updated and processed Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

19. Sensor input brf beliefs Generate options desires filter intentions action Generic BDI Architecture Action output Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

20. Architecture of BDI-Based Agent Execution Cycle: • New information arrives that updates beliefs and goals • Actions are triggered by new beliefs or goals • A triggered action is intended • An intended action is selected • The selected intention is activated • An action is performed • New beliefs or goals are stored • Intentions are updated Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

21. Web Ontology Language for Services (OWL-S) An OWL-S service description provides • Declarative ads for properties and capabilities, used for discovery • Declarative APIs, used for execution • A declarative description of services • Based on their inputs, outputs, preconditions, and effects • Used for composition and interoperation Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

22. OWL-S Example: Processing Book Orders Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

23. OWL-S IOPE’s for Bookstore Example Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

24. Composition as Planning • Service composition can be framed as an automatic planning problem: • States of the world (current and desired) can be represented formally • Each service invocation corresponds to an action, modeled with inputs, outputs, preconditions, and effects • A composed service is like a plan that invokes the constituent services under suitable constraints of control and data flow Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

25. Rules: Logical Representations • Rules are desirable because they are • Modular: easy to read and maintain • Inspectable: easy to understand • Executable: no further translation needed • Expressive: (commonly) Turing complete and can capture knowledge that would otherwise not be captured declaratively • Compare with relational calculus (SQL) or description logics (OWL) • Declarative, although imperfectly so Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

26. Kinds of Rules • Reaction or (ECA) • On event if condition then perform action • Derivation rules: special case of above • Integrity constraints: derive false if error • Inference rules • If antecedent then consequent • Support multiple computational strategies • Forward chaining; backward chaining Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

27. Applying Reaction Rules • Capture protocols, policies, and heuristics as rules • Examples? • Often, combine reaction with inference rules (to check if a condition holds) • Modeling challenge • What defines an event? • How to capture composite events by pushing event detection to lower layers Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

28. Applying Inference Rules • Inference rules capture general requirements well • Elaboration tolerance requires defeasibility • Write general rules • Override them as need to specialize them to account for context • Leads to logical nonmonotonicity • Easy enough operationally but difficult to characterize mathematically • Details get into logic programming with negation Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

29. Use of Variables • Need free variables to make the rules generic in how they apply • In event and condition for ECA rules • In antecedent for inference rules • Should generally not have free variables in consequent to ensure “safety” • Free variable in action indicates perform action for each binding • Free variable in consequent means assert it for each binding Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

30. Section Summary • Agents provide the flexibility that realizes the benefits of SOC • Agents come with sophisticated abstractions that are closer to humanly expressed and understood requirements • Agents go beyond objects and procedural programming, and are supported by various programming methods • Self-study Jess Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns