Chapter 16: Multiagent Systems Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005.

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Chapter 16: Multiagent Systems Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005

Chapter 162Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Highlights of this Chapter Applicability in Service-Based Systems Multiagent Architecture Agent Types Lifecycle Management Consistency Maintenance Modeling Other Agents Cognitive Concepts

Chapter 163Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Attributes of Multiagent Systems Decentralization Complex components, often best described at the knowledge level Adaptive behavior Complex interactions Coordination Emergent, aggregate behaviors

Chapter 164Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Dimensions of MAS: System Scale (the number of agents): Interactions: Coordination (self interest): Agent Heterogeneity: Communication Paradigm: IndividualCommitteeSociety ReactivePlanned AntagonisticAltruisticCollaborative CompetitiveCooperativeBenevolent IdenticalUnique Point-to-PointMulti-by-name/roleBroadcast

Chapter 165Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Basic Problems of MAS Description, decomposition, and distribution of tasks among agents Interaction and communication among agents Distribution of control among agents Representation of goals, problem-solving states, and other agents Rationality, consistency maintenance, and reconciliation of conflicts among agents

Chapter 166Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Principles of Agent Systems Understand the principles to engineer agent-based systems System architecture Low-level interoperation Information systems Protocols and compliance Underlying frameworks and implementations

Chapter 167Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns (de facto) Standard Agent Types

Chapter 168Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Name Service A multiagent architecture requires scalable, symbolic name resolution Alternative naming protocols FIPA LDAP Jini CORBA Naming Service JNDI

Chapter 169Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Directory Service Simple yellow-page service Registered agents advertise their services by providing their name, address, and service description Agents request recommendations for available services (provided by other registered agents or services) A simple database-like mechanism that allows agents to insert descriptions of the services they offer query for services offered by other agents. 1..n Directory Service Agents on a LAN Brokerage, recruitment and mediation services are not provided by Directory Service

Chapter 1610Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Agent Framework Services (CoABS)

Chapter 1611Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Brokerage Service Beyond UDDI Cooperates with a Directory Service An agent requests the Brokerage Service to recruit one or more agents who can provide a service Brokerage Service uses knowledge about the requirements and capabilities of registered agents to Determine the appropriate agents to which to forward a request for a service Negotiates with the agents to determine a suitable set of service providers Potentially learn about the properties of the responses example: Brokerage agent determines that advertised results from agent X are incomplete and seeks a substitute for X

Chapter 1612Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns FIPA FIPA is the Foundation for Intelligent Physical Agents, with website at Specifies standards for heterogeneous, interoperating agent-based systems. Concerned with agency as it relates to 1. Autonomy (goal-driven) 2. Communal integration; mostly communication, but also cooperation.

Chapter 1613Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Agent Management System: 1

Chapter 1614Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Agent Management System: 2 Handles the creation, registration, location, communication, migration and retirement of agents. Provides the following services: White pages, such as agent location, naming and control access services, which are provided by the Agent Management System (AMS). Agent names are represented by a flexible and extensible structure called an agent identifier, which can support social names, transport addresses, name resolution services, amongst other things Yellow pages, such as service location and registration services, which are provided by the Directory Facilitator (DF) Agent message transport services

Chapter 1615Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns FIPA-Compliant Agent Frameworks Some of the popular, FIPA-compliant agent frameworks used for designing multiagent systems: FIPA-OS, JADE, Zeus,

Chapter 1616Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Consistency Maintenance across Services A truth maintenance system (TMS) performs a form of propositional deduction maintains justifications and explains the results of its deductions updates beliefs incrementally when data are added or removed uses its justifications to perform dependency-directed backtracking TMSs are important because they deal with atomicity deal with the frame problem lead to efficient search

Chapter 1617Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Architecture of TMS-Based Agent The problem solver represents domain knowledge in the form of rules, procedures, etc. and chooses what to focus on next The TMS keeps track of the current state of the search for a solution. It uses constraint satisfaction to maintain consistency in the inferences made by the problem solver Problem Solver TMS justifications beliefs

Chapter 1618Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Knowledge Base Integrity Stability: believe everything justified validly; disbelieve everything justified invalidly Well-Foundedness: beliefs are not circular Logical consistency: logical contradictions do not exist Completeness: a system will find a consistent state if it exists, or report failure Problems arise when knowledge is distributed

Chapter 1619Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Degrees of Logical Consistency Inconsistency: one or more agents are inconsistent Local Consistency: agents are locally consistent Local-and-Shared Consistency: agents are locally consistent and all agents agree about shared data Global Consistency: agents are globally consistent The DTMS maintains local-and-shared consistency and well foundedness

Chapter 1620Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Distributed TMS Each agent has a justification-based TMS Each datum can have status OUT, IN (valid local justification), or EXTERNAL. A shared datum must be IN to one of the agents that shares it When a problem solver adds or removes a justification, the DTMS Unlabels data based on the changed justification Labels all unlabeled shared data Chooses labels for remaining unlabeled data; if this fails, it backtracks by unlabeling additional data and iterating

Chapter 1621Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cooperative Service: 1 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r2: recommend(X) :- takeover-bid(X) IN r1: takeover-bid(X) :- cash-rich(X) IN ? recommend(?X)

Chapter 1622Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cooperative Service: 2 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN Shared with: Client; Justification: (f2 r1 r2) recommend(XCorp)

Chapter 1623Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cooperative Service: 3 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) EXTERNAL Shared with: Broker; Justification: ( ) f5: buy(xcorp) IN Justification: (f3 f4 r3) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN Shared with: Client; Justification: (f2 r1 r2)

Chapter 1624Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cooperative Service: 4 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) EXTERNAL Shared with: Broker; Justification: ( ) f5: buy(xcorp) IN Justification: (f3 f4 r3) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN --> OUT r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN --> OUT Shared with: Client; Justification: (f2 r1 r2) relabel recommend(XCorp)

Chapter 1625Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cooperative Service: 5 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) OUT Shared with: Broker; Justification: ( ) f5: buy(xcorp) OUT Justification: (f3 f4 r3) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) OUT r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) OUT Shared with: Client; Justification: (f2 r1 r2)

Chapter 1626Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Asimov’s Laws of Robotics 0. A robot may not injure humanity or, through inaction, allow humanity to come to harm. [Added after the following more famous laws] 1. A robot may not injure a human being, or, through inaction, allow a human being to come to harm. 2. A robot must obey the orders given it by human beings except where such orders would conflict with the First Law. 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

Chapter 1627Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Cognitive Economy Prefer the simpler (more economical) explanation ("but not too simple" - Einstein) Essential because agents have limited reasoning capacities Agents must finitely represent their environment themselves and others themselves and others representing them and others, ad infinitum Zero-order model: others are similar to oneself

Chapter 1628Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns “Practical” Economy In simple terms, cognitive economy has two consequences on how agents act Agents should act predictably Agents should act the way they want others to act These are examples of universalizable principles as advocated by Kant, and provide a rational basis for ethical and social behavior

Chapter 1629Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns An Agent Should Act Benevolently seeking the welfare of others Rationally consistent with its model of itself Predictably consistent with its model of other agents’ beliefs about itself

Chapter 1630Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Benevolence: “A Mattress in the Road” Who will stop to pick it up?

Chapter 1631Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Information System Example: A Collective Store Benevolent agents might contribute information they have retrieved, filtered, and refined to a collective store Utilitarian variant: Access to the collective store might be predicated on contributions to it Collective Store World Wide Web... Query Agents

Chapter 1632Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Challenges Doing the "right" thing Autonomy Conventions: emergence and maintenance Coordination Collaboration Communication: semantics and pragmatics Interaction-oriented programming

Chapter 1633Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns Chapter 16 Summary