The mission of the Agent Platform Special Interest Group (Agent PSIG) is to work with OMG platform and domain task forces:
• To identify and recommend new OMG specifications in the area of agent technology.
• To recommend agent-related extensions to existing and emerging OMG specifications
• To promote standard agent modeling languages and techniques that increase rigor and consistency of specifications.
• To enable developers to better understand how to develop agent-based applications, including large-scale distributed agent systems.
• To leverage and interoperate with other OMG specifications in the agent area, where appropriate.
• To liaise with related organizations that share common goals.
James J. Odell
[email protected] (emeritus)
Mailing list: firstname.lastname@example.org
There will be OMG meetings starting soon.
A history of the earlier Agent PSIG meeting can be viewed at http://www.objs.com/agent/index.html.
Previous efforts at: https://www.omgwiki.org/AMP-team and https://www.omgwiki.org/EMP-team
What is an Agent?
In general, agents can be software agents, hardware agents, firmware agents, robotic agents, human agents, and so on. While software developers naturally think of IT systems as being constructed of only software agents, a combination of agent mechanisms might in fact be used from shop-floor manufacturing to warfare systems.
Agents and AI
The purpose of an Agent to specify a classification of autonomous entities (agent instances) that can adapt to and interact with their environment, and to specify the features, constraints, and semantics that characterize those agent instances. Agents deployed for IT systems generally should have the following three important properties:
• Autonomous - is capable acting without direct external intervention. Agents have some degree of control over their internal state and can act based on their own experiences. They can also possess their own set of internal responsibilities and processing that enable them to act without any external choreography–which and range from very simple coding to very complex techniques). As such, they can act in reactive and proactive ways. When an agent acts on behalf of (or as a proxy for) some person or thing, its autonomy is expected to embody the goals and policies of the entity that it represents. In UML terms, agents can have classifier behavior that governs the lifecycle of the agent.
• Interactive - communicates with the environment and other agents. Agents are interactive entities because they are capable of exchanging rich forms of messages with other entities in their environment. These messages can support requests for services and other kinds of resources, as well as event detection and notification. They can be synchronous or asynchronous in nature. The interaction can also be conversational in nature, such as negotiating contracts, marketplace-style bidding, or simply making a query or message call to another object. In the Woodridge-Jennings definition of agency, this property is referred to as social ability.
• Adaptive - capable of responding to other agents and/or its environment. Agents can react to messages and events and then respond in a timely and appropriate manner. Agents can be designed to make difficult decisions and even modify their behavior based on their experiences. They can learn and evolve. In the Woodridge-Jennings definition of agency, this property is referred to as reactivity and proactivity.
These properties are mainly covered by a set of core aspects each focusing on different viewpoints of an agent system. Even if these aspects do not directly appear in the SoaML metamodel, we can relate them to SoaML-related concepts. Depending on the viewpoint of an agent system, various aspects are prominent. Even if these aspects do not directly appear in the SoaML metamodel, we can relate them to SoaML-related concepts.
• Agent aspect – describes single autonomous entities and the capabilities each can possess to solve tasks within an agent system. In SoaML, the stereotype Agent describes a set of agent instances that provides particular service capabilities.
• Collaboration aspect – describes how single autonomous entities collaborate within the multiagent systems (MAS) and how complex organizational structures can be defined. In SoaML, a ContractFulfillment (CollaborationUse) indicates which roles are interacting (i.e., which parts they play) in the contract. Collaboration can involve situations such as cooperation and competition.
• Role aspect – covers feasible specializations and how they could be related to each role type. In SoaML, the concept of a role is especially used in the context of service contracts. Like in agent systems, the role type indicates which responsibilities an actor has to take on.
• Interaction aspect – describes how the interaction between autonomous entities or groups/organizations take place. Each interaction specification includes both the actors involved and the order which messages are exchanged between these actors in a protocol-like manner. In SoaML, contracts take the role of interaction protocols in agent systems. Like interaction protocols, a services contract takes a role centered view of the business requirements which makes it easier to bridge the gap between the process requirements and message exchange.
• Behavioral aspect – describes how plans are composed by complex control structures and simple atomic tasks such as sending a message and specifying information flows between those constructs. In SoaML, a ServiceInterface is a BehavioredClassifier and can thus contain ownedBehaviors that can be represented by UML2 Behaviours in the form of an Interaction, Activity, StateMachine, ProtocolStateMachine, or OpaqueBehavior.
• Organization/Group aspect – Agents can form social units called groups. A group can be formed to take advantage of the synergies of its members, resulting in an entity that enables products and processes that are not possible from any single individual.