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Categories of Agent Research
HumanIntelligence
IdealIntelligence
Reasoning Agents that think likehumans(cognitive science)
Agents that thinkrationally(logic)
Behavior Agents that act likehumans(Turing test)
Agents that behaverationally(“do the right thing”)
What Is an Agent?
In general, an agent is an active computational entity• with a persistent identity• that can perceive, reason about, and initiate
activities in its environment• that can communicate (with other agents)
Roles of AgentsAgents can serve several roles in information systems. Each
role can have different variants• As client
– does everything itself– tells a server how to do something– tells a server what the client would like to have done
• As server– does nothing– does exactly as told– satisfies high-level requests– preserves self-interest
• As contents of messages– embodies all of client's functionality– is a procedural script– is a declarative specification
Agent Characteristics/1
• Locality: local or remote• Uniqueness: homogeneous or heterogeneous• Granularity: fine- or coarse-grained• Persistence: transient or long-lived• Level of Cognition: reactive or deliberative• Sociability: autistic, aware, responsible, team player• Friendliness: cooperative or competitive or antagonistic• Construction: declarative or procedural• Semantic Level: communicate what or how• Mobility: stationary or itinerant
Agent Characteristics/2• Autonomy: independent or controlled• Adaptability: fixed or teachable or autodidactic• Sharing: degree and flexibility with respect to
– communication: vocabulary, language, protocol– intellect: knowledge, goals, beliefs, specific ontologies– skills: procedures, "standard" behaviors, implementation
languages
• Interactions: direct or via facilitators, mediators, or “nonagents”
• Interaction Style/Quality/Nature: with each other or with “the world”, or both?
• Do the agents model their environment, themselves, or other agents?
A Rational Agent
Rationality depends on...• The performance measure for success• 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
A Simple Reactive Agent
Agent
En
vironm
ent
Sensors
Effectors
What the worldis like now
What action Ishould do now
Condition-action rules
A Simple Reactive Agent
function Simple-Reactive-Agent(percept)static: rules, a set of condition-action rules
state Interpret-Input(percept)rule Rule-Matching(state, rules)action Rule-Action(rule)return action
A Reactive Agent with State
Agent
En
vironm
ent
Sensors
Effectors
What the worldis like now
What action Ishould do now
Condition-action rules
State
How the world evolves
What my actions do
function Reactive-Agent-with-State(percept) static: rules, a set of condition-action rules state, a description of the current world state Update-State(state, percept) rule Rule-Matching(state, rules) action Rule-Action(rule) state Update-State(state, action) return action
A Reactive Agent with State
A Goal-Based Agent
Agent
En
vironm
ent
Sensors
Effectors
What the worldis like now
What action Ishould do now
Goals
State
How the world evolves
What my actions doWhat it will be likeif I do action A
A Utility-Based Agent
Agent
En
vironm
ent
Sensors
Effectors
What the worldis like now
What action Ishould do now
Utility
State
How the world evolves
What my actions doWhat it will be likeif I do action A
How happy I willbe in such a state
A Utility-Based Agent
function Utility-Based-Agent(percept)static: a set of probabilistic beliefs about the state of the world
Update-Probs-for-Current-State(percept,old-action)Update-Probs-for-Actions(state, actions)Select-Action-with-Highest-Utility(probs)return action
Agent Environments• Communication Infrastructure
– Shared memory (blackboard)– Connected or Connectionless (email)– Point-to-Point, Multicast, or Broadcast– Directory Service
• Communication Protocol– KQML– HTTP and HTML– OLE, CORBA, DCOM, etc.
• Interaction Protocol• Mediation Services• Security Services (timestamps/authentication/currency)• Remittance Services• Operations Support
(archiving/billing/redundancy/restoration/accounting)
Agent Environments
• Accessible vs. Inaccessible• Deterministic vs. Nondeterministic• Episodic vs. Nonepisodic• Static vs. Dynamic• Discrete vs. Continuous
Open information environments (e.g., InfoSleuth) are inaccessible, nondeterministic, nonepisodic, dynamic, and discrete
Mediators
Modules that exploit encoded knowledge about data to create information for higher-level applications. Mediators, thus,
• provide logical views of the underlying information
• reside in an active layer between applications and resources
• are small, simple, and maintainable independently of others
• are declaratively specified, where possible, and inspectable by users
• come in a wide range of capabilities, from database and protocol converters, to intelligent modules that capture the semantics of the domain and learn from the data
Mediator ArchitectureApplication Programs
Information Resources
User Interfaces
NetworksNetwork Interfacesand Mediators
Mediator Interfaces
• Mediators should be separate from databases– mediators contain knowledge beyond the scope of a database– mediators contain abstractions that are not part of a database– mediators must deal with uncertainty– mediators access multiple databases to combine disjoint data
• Mediators should be separate from applications– their functions are different in scope than those of applications– separate mediators are easier to maintain
• Because mediators are stable and small, they can be mobile– they can be shipped to sites where large volumes of data must be
processed
Learning in Mediators
Learning can be driven by• feedback from performance measures• explicit induction over information resources
Result of learning can be• modifications to certainty parameters• augmented tabular knowledge• new symbolic concepts
Type BrokersA means to manage structure and semantics of information
and query languages. Define standard types by which computations can communicate. Most of this work pertains to lower level issues than CIS
Typically these involve a set of type servers or brokers and a way to distribute type information. An application uses the broker to find a service, and then communicates directly with the desired service
Brokers give slightly more semantics than directories--the type signature of methods, not just their names
With more sophisticated notions of service semantics, these could be more useful
Protocol Handlers• Mediators [Wiederhold]
• Aides [Carnot DCA]
• Database and Protocol Agents [Carnot ESS]
• Heads [Steiner]
• Brokers [OMNI]
• Knowledge handlers [COSMO]
• Intelligent information agents [Papazoglou]
• Front-end processors [Hecodes]
• Integrating agents, routers, and wrappers [Gray]
• Facilitators [ARPA Knowledge Sharing Effort]