In the race for automation, distributed systems are required to perform increasingly complex
reasoning to deal with dynamic tasks, often not controlled by humans. On the one hand …

The BDI model forms the basis of much of the research on symbolic models of agency and
agent-oriented software engineering. While many variants of the basic BDI model have been …

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 …

An important issue in deploying an autonomous system is how to enable human users and
stakeholders to develop an appropriate level of trust in the system. It has been argued that a …

The continuous integration of software-intensive systems together with the ever-increasing
computing power offer a breeding ground for intelligent agents and multi-agent systems …

Recent work in multi-agent intention scheduling has shown that enabling agents to predict
the actions of other agents when choosing their own actions may be beneficial. However …

The emergence of social norms has attracted much interest in a wide array of disciplines,
ranging from social science and cognitive science to artificial intelligence. In this paper, we …

Abstract Belief–desire–intention (BDI) agents are a popular agent architecture. We extend
conceptual agent notation (Can)—a BDI programming language with advanced features …

There has been considerable progress in both the theory and practice of agent
programming since Georgeff and Rao's seminal work on the belief-desire-intention …

User-supplied domain control knowledge in the form of hierarchically structured Goal-Plan
Trees (GPTs) is at the heart of a number of approaches to reasoning about action …