Agent programming in the cognitive era
Rafael H. Bordini,Amal El Fallah Seghrouchni,Koen V. Hindriks,Brian Logan,Alessandro Ricci +4 more
- Vol. 34, Iss: 2, pp 1-31
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TLDR
It is argued that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems.Abstract:
It is claimed that, in the nascent ‘Cognitive Era’, intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we explore the contributions that agent-oriented programming can make to the development of future intelligent systems. We briefly review the state of the art in agent programming, focussing particularly on BDI-based agent programming languages, and discuss previous work on integrating AI techniques (including machine learning) in agent-oriented programming. We argue that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems. We identify a range of possible approaches to integrating AI into a BDI agent architecture. Some of these approaches, e.g., ‘AI as a service’, exploit immediate synergies between rapidly maturing AI techniques and agent programming, while others, e.g., ‘AI embedded into agents’ raise more fundamental research questions, and we sketch a programme of research directed towards identifying the most appropriate ways of integrating AI capabilities into agent programs.read more
Citations
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Automated Planning: Theory and Practice.
TL;DR: A translation apparatus is provided which comprises an inputting section for inputting a source document in a natural language and a layout analyzing section for analyzing layout information.
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A Review of Agent-Based Programming for Multi-Agent Systems
TL;DR: Agent programming is a sub-area of symbolic artificial intelligence where agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents).
Proceedings Article
An AgentSpeak meta-interpreter and its applications
TL;DR: A meta-interpreter for the AgentSpeak language is given, its correctness is proved, and it is shown how the meta-Interpreter can be used to extend the Agent Speak language and to add features to the implementation.
Proceedings ArticleDOI
A Multi-Agent Approach to Combine Reasoning and Learning for an Ethical Behavior
TL;DR: This paper draws upon existing works to propose a novel hybrid method using symbolic judging agents to evaluate the ethics of learning agents' behaviors, and accordingly improve their ability to ethically behave in dynamic multi-agent environments.
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