Publications

This thesis aims to provide a comprehensive framework for creating more adaptive and resilient autonomous agents, capable of operating effectively in dynamic and

unpredictable environments. In pursuit of this aim, this thesis makes four main contributions. A formal semantics for actions with explicit durations, pre-conditions, post-conditions, and terminating conditions; a method for detecting persistent action failures using a recorded history of action execution outcomes; a method for learning new action descriptions; and a cohesive implementation that combines these three contributions with a framework for reconfiguring agent plan libraries.

In this paper we present an extension of Belief-Desire-Intention agents which can adapt their performance in response to changes in their environment. We consider situations in which the agent’s actions no longer perform as anticipated. Our agents maintain explicit descriptions of the expected behaviour of their actions, are able to track action performance, learn new action descriptions and patch affected plans at runtime. Our main contributions are the underlying theoretical mechanisms for data collection about action performance, the synthesis of new action descriptions from this data and the integration with plan reconfiguration. The mechanisms are supported by a practical implementation to validate the approach.

In this paper, we present an extension of Belief-Desire-Intention agents which can adapt their performance in response to changes in their environment. Our main contributions are the underlying theoretical mechanisms for data collection about action performance, the synthesis of new action descriptions from this data, the integration with plan reconfiguration, and a practical implementation to validate the semantics.

In this paper, an extension of the semantics for action execution in the Gwendolen BDI programming language is presented. The semantics introduce duration and terminating conditions for robotic actions. The implementation is written in Java within the Gwendolen programming language source code.

In this extended abstract, an extension for agent programming languages is proposed. Primarily, the implications for the language operational semantics are discussed, with consideration for related work.

In this paper, a system architecture for Belief-Desire-Intention (BDI) autonomous agents capable of adapting to changes in a dynamic environment is described alongside an outline of the required research. Specifically, an agent-maintained self-model with accompanying theories of durative actions is described, with a method for learning new action descriptions in BDI systems.