2APL (A Practical Agent Programming Language) is a modular BDI-based programming language that supports the development of multi-agent systems. 2APL provides a rich set of programming constructs allowing direct implementation of concepts such as beliefs, declarative goals, actions, plans, events, and reasoning rules. The reasoning rules allow run-time selection and generation of plans based on declarative goals, received events and messages, and failed plans. 2APL can be used to implement muti-agent systems consisting of software agents with reactive as well as pro-active behaviours.
2APL provides programming constructs to specify both multi-agent systems and individual agents. Multi-agent systems are specified in terms of individual agents and the environments with which they interact. Individual agents are specified in terms of the following ingredients.
The 2APL Platform and its corresponding Eclipse plug-in editor are developed to facilitate the development and execution of multi-agent programs. The execution of an individual 2APL agent program is realized by a cyclic sense-reason-act process, called the deliberation process. The execution of a 2APL multi-agent program is the parallel executions of the involved individual agent programs.
Prolog is a logic programming language that has its origins in artificial intelligence and computational linguistics.
Distributed Artificial Intelligence (DAI) also called Decentralized Artificial Intelligence is a subfield of artificial intelligence research dedicated to the development of distributed solutions for problems. DAI is closely related to and a predecessor of the field of multi-agent systems.
In computer science, a software agent is a computer program that acts for a user or another program in a relationship of agency.
Soar is a cognitive architecture, originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University. It is now maintained and developed by John Laird's research group at the University of Michigan.
A decentralised system in systems theory is a system in which lower level components operate on local information to accomplish global goals. The global pattern of behaviour is an emergent property of dynamical mechanisms that act upon local components, such as indirect communication, rather than the result of a central ordering influence of a centralised system.
The belief–desire–intention software model (BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans and executing those plans. A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.
In artificial intelligence, an intelligent agent (IA) is an agent acting in an intelligent manner; It perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or acquiring knowledge. An intelligent agent may be simple or complex: A thermostat or other control system is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome.
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behavior.
An Abstract Agent Programming Language or Artificial Autonomous Agents Programming Language or 3APL is an experimental tool and programming language for the development, implementation and testing of multiple cognitive agents using the Belief-Desire-Intention (BDI) approach.
In artificial intelligence, a procedural reasoning system (PRS) is a framework for constructing real-time reasoning systems that can perform complex tasks in dynamic environments. It is based on the notion of a rational agent or intelligent agent using the belief–desire–intention software model.
GOAL is an agent programming language for programming cognitive agents. GOAL agents derive their choice of action from their beliefs and goals. The language provides the basic building blocks to design and implement cognitive agents by programming constructs that allow and facilitate the manipulation of an agent's beliefs and goals and to structure its decision-making. The language provides an intuitive programming framework based on common sense or practical reasoning.
AgentSpeak is an agent-oriented programming language. It is based on logic programming and the belief–desire–intention software model (BDI) architecture for (cognitive) autonomous agents. The language was originally called AgentSpeak(L), but became more popular as AgentSpeak, a term that is also used to refer to the variants of the original language.
JACK Intelligent Agents is a framework in Java for multi-agent system development. JACK Intelligent Agents was built by Agent Oriented Software Pty. Ltd. (AOS) and is a third generation agent platform building on the experiences of the Procedural Reasoning System (PRS) and Distributed Multi-Agent Reasoning System (dMARS). JACK is one of the few multi-agent systems that uses the BDI software model and provides its own Java-based plan language and graphical planning tools.
Agent-oriented programming (AOP) is a programming paradigm where the construction of the software is centered on the concept of software agents. In contrast to object-oriented programming which has objects at its core, AOP has externally specified agents at its core. They can be thought of as abstractions of objects. Exchanged messages are interpreted by receiving "agents", in a way specific to its class of agents.
Deliberative agent is a sort of software agent used mainly in multi-agent system simulations. According to Wooldridge's definition, a deliberative agent is "one that possesses an explicitly represented, symbolic model of the world, and in which decisions are made via symbolic reasoning".
The Multi-Agent Programming Contest is an annual international programming competition with stated goal of stimulating research in the area of multi-agent system development and programming.
In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems.
The SARL programming language is a modular agent-oriented programming language. It aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralization, reactivity, autonomy and dynamic reconfiguration.
Human-Robot Collaboration is the study of collaborative processes in human and robot agents work together to achieve shared goals. Many new applications for robots require them to work alongside people as capable members of human-robot teams. These include robots for homes, hospitals, and offices, space exploration and manufacturing. Human-Robot Collaboration (HRC) is an interdisciplinary research area comprising classical robotics, human-computer interaction, artificial intelligence, process design, layout planning, ergonomics, cognitive sciences, and psychology.
GOLOG is a high-level logic programming language for the specification and execution of complex actions in dynamical domains. It is based on the situation calculus. It is a first-order logical language for reasoning about action and change. GOLOG was developed at the University of Toronto.