Agent programming in the cognitive era

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...

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Veröffentlicht in:Autonomous agents and multi-agent systems Jg. 34; H. 2
Hauptverfasser: Bordini, Rafael H., El Fallah Seghrouchni, Amal, Hindriks, Koen, Logan, Brian, Ricci, Alessandro
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.10.2020
Schlagworte:
20th Anniversary Special Issue
Artificial Intelligence
Computer Science
Computer Systems Organization and Communication Networks
Software Engineering/Programming and Operating Systems
User Interfaces and Human Computer Interaction
Viewpoint
Agent programming languages
Belief-desire-intention
Artificial intelligence
Machine learning
ISSN:1387-2532, 1573-7454
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Zusammenfassung: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.
ISSN:1387-2532
1573-7454
DOI:10.1007/s10458-020-09453-y