Agent Programming Languages and Logics in Agent-Based Simulation

Larsen, John Bruntse

doi:10.1007/978-3-319-76081-0_44

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…Perhaps the key contribution of the BDI-based approach, at least compared to agents where programs are learned, is the intelligibility of the resulting agent behaviour by end users and other stakeholders, see, e.g., [26,88,108,128]. This has been termed Explainable AI (XAI) [69], i.e., the development of autonomous systems capable of explaining their decisions and actions to human users.…”

Section: Key Contributions and Limitations Of The Current Bdi Modelmentioning

confidence: 99%

Agent programming in the cognitive era

Bordini

Seghrouchni

Hindriks

et al. 2020

Auton Agent Multi-Agent Syst

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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.

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Section: Key Contributions and Limitations Of The Current Bdi Modelmentioning

confidence: 99%

Agent programming in the cognitive era

Bordini

Seghrouchni

Hindriks

et al. 2020

Auton Agent Multi-Agent Syst

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“…In particular the BDI programming paradigm, which is also supported in GAMA, is a simple tool for modeling human reasoning in the agents. As argued in [1] however, the advances made in AI with frameworks and metamodels for agent environments and social systems could be further leveraged in agent-based simulation. In particular, the AORTA framework for adding organizational reasoning to agents can be useful for studying environments where humans enact roles and solve objectives of an organization.…”

Section: Introductionmentioning

confidence: 99%

Adding Organizational Reasoning to Agent-Based Simulations in GAMA

Larsen

2019

Engineering Multi-Agent Systems

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“…This paper is an extension of Larsen (2018) presented at ACIIDS 2018, which presents an analysis and evaluation of using recent advances in agent programming languages and logics, in particular frameworks for implementing social behaviour, in ABS. Our objective is to highlight inherent limitations of using BDI for social simulation that can be adressed by using the AORTA framework for organizational reasoning.…”

Section: Introductionmentioning

confidence: 99%

Going beyond BDI for agent-based simulation

Larsen

2019

Journal of Information and Telecommunication

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Research in multi-agent systems has resulted in agent programming languages and logics that are used as a foundation for engineering multi-agent systems. Research includes reusable agent programming platforms for engineering agent systems with environments, agent behaviour, communication protocols and social behaviour, and work on verification. Agent-based simulation is an approach for simulation that also uses the notion of agents. Although agent programming languages and logics are much less used in agent-based simulation, there are successful examples with agents designed according to the BDI paradigm, and work that combines agent-based simulation platforms with agent programming platforms. This paper analyses and evaluates benefits of using agent programming languages and logics for agent-based simulation. In particular, the paper considers the use of agent programming languages and logics in a case study of simulating emergency care units.

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Agent Programming Languages and Logics in Agent-Based Simulation

Cited by 6 publications

References 27 publications

Agent programming in the cognitive era

Agent programming in the cognitive era

Adding Organizational Reasoning to Agent-Based Simulations in GAMA

Going beyond BDI for agent-based simulation

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