Service-Oriented Computing: Semantics, Processes, Agents August 2004 Chapter 15: Agents Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005 © Singh & Huhns

Highlights of this Chapter Service-Oriented Computing: Semantics, Processes, Agents August 2004 Highlights of this Chapter Agents Introduced Agent Descriptions Abstractions for Composition Describing Compositions Service Composition as Planning Rules Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns © Singh & Huhns

Service-Oriented Computing: Semantics, Processes, Agents August 2004 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 Business partners => agents Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns © Singh & Huhns

Agents and MAS for SOC Why agents for services? Unlike objects, agents Autonomy, heterogeneity, dynamism Unlike objects, agents Are proactive and autonomous Cooperate or compete Model users, themselves, others Dynamically use and reconcile ontologies Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Modeling Agents: MAS Emphasize interaction Social: about collections of agents Organizational: about teams and groups Legal: about contracts and compliance Ethical: about right and wrong actions Emphasize autonomy and communication Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Mapping SOC to Agents Agents as components of an open system Autonomy => ability to enter into and enact contracts; compliance Heterogeneity => ontologies Loose coupling => communication Trustworthiness => contracts, ethics, learning, incentives Dynamism => combination of the above Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

A Reactive Agent Environment e; RuleSet r; while (true) { state = senseEnvironment(e); a = chooseAction(state, r); e.applyAction(a); } Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Service-Oriented Computing: Semantics, Processes, Agents August 2004 A Rational Agent Rationality depends on ... A performance measure, e.g., expected utility What the agent has perceived so far What the agent knows ahead of time 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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns © Singh & Huhns

Logic-Based Agents An agent is a knowledge-based system Challenges: Explicitly represents symbolic model of the world Reasons symbolically via logical deduction Challenges: Maintaining adequate descriptions of the world Representing information about complex real-world entities in symbolic terms Easier in information environments than in general Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Cognitive Architecture for an Agent For SOC, sensors and effectors are services; communication is via messaging middleware Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Generic BDI Architecture brf Generate options filter action Sensor input beliefs desires intentions A BDI architecture addresses how beliefs, desires and intentions are represented, updated, and acted upon Action output Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Architecture of BDI-Based Agent Execution Cycle: the agent Receives new information Updates beliefs and goals Reasons about actions Intends an action Selects an intended action Activates selected intention Performs an action Updates beliefs, goals, intentions Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

OWL-S Service Ontology Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

OWL-S Compared to UDDI Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

OWL-S Service Model Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

OWL-S Example: Processing Book Orders Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

OWL-S IOPEs for Bookstore Example Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Composition as Planning Service composition as planning: Represent current and goal states Represent each service as an action (with inputs, outputs, preconditions, effects) Represent a composed service as a plan that invokes the constituent services constraining the control and data flow to achieve the goal state Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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 (classical SQL) or description logics (OWL) Declarative, although imperfectly so Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Kinds of Rules ECA or Reaction Derivation rules: special case of above 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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Applying ECA Rules Capture protocols, policies, and heuristics as rules Examples? Often, combine ECA with inference rules (to check if a condition holds) Modeling challenge What is an event? How to capture composite events by pushing event detection to lower layers Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Use of Variables Need free variables to make the rules generic in how they apply For ECA rules: event and condition For inference rules: antecedent 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 Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

Service-Oriented Computing: Semantics, Processes, Agents August 2004 Chapter 15 Summary Agents are natural fit with open environments Agent abstractions support expressing requirements in a natural manner Agents go beyond objects and procedural programming Self-study Jess Chapter 15 Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns © Singh & Huhns