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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 (providing methods with variable parameters) at its core, AOP has externally specified agents (with interfaces and messaging capabilities) at its core.
Agent-oriented software engineering (AOSE) is a new software engineering paradigm that arose to apply best practice in the development of complex Multi-Agent Systems (MAS) by focusing on the use of agents, and organizations (communities) of agents as the main abstractions.
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 ...
Agent-oriented programming; Aspect-oriented programming (AOP) Convention over configuration; Component-based software engineering; Functional programming (FP) Hierarchical object-oriented design (HOOD) [16] Literate programming; Logic programming; Modular programming; Object-oriented programming (OOP) Procedural programming; Reactive programming
Java Agent Development Framework, or JADE, is a software framework for the development of software agents, implemented in Java.JADE system supports coordination between several agents FIPA and provides a standard implementation of the communication language FIPA-ACL, which facilitates the communication between agents and allows the services detection of the system.
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. [1] SARL is platform-independent and agent's architecture-agnostic.
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A multi-agent system may contain combined human-agent teams. Agents can be divided into types spanning simple to complex. Categories include: Passive agents [11] or "agent without goals" (such as obstacle, apple or key in any simple simulation) Active agents [11] with simple goals (like birds in flocking, or wolf–sheep in prey-predator model)