Agent programming in the cognitive era

Rafael H. Bordini, Amal El Fallah Seghrouchni, Koen Hindriks, Brian Logan*, Alessandro Ricci

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Article number37
Pages (from-to)1-31
Number of pages31
JournalAutonomous Agents and Multi-Agent Systems
Volume34
Issue number2
Early online date12 May 2020
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Agent programming languages
  • Artificial intelligence
  • Belief-desire-intention
  • Machine learning

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