1. 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

2. 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

3. 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

4. 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

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
Chapter 15
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
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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

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

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

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

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

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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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