Abstract In Hierarchical Task Network (HTN) planning, compound tasks need to be refined
into executable (primitive) action sequences. In contrast to their primitive counterparts …

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 …

Modern computer games typically have a huge interaction spaces and non-deterministic
environments. Automation in testing can provide a vital boost in development and it further …

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 …

The Belief Desire Intention (BDI) model of agency is a popular and mature paradigm for
designing and implementing multiagent systems. There are several agent implementation …

Recently, inferred effects of compound (totally ordered) HTN planning tasks were
introduced. Guaranteed effects are those which hold true after all executable refinements of …

We propose a new approach to intention progression in multi-agent settings where other
agents are effectively black boxes. That is, while their goals are known, the precise …

One of the key advantages of Belief-Desire-Intention (BDI) agents [7] is their ability to pursue
multiple goals in parallel. When multiple goals are pursued at the same time, an agent has …

Agents have been applied to a wide variety of fields, including power systems and
spacecraft. Belief-Desire-Intention (BDI) agents, as one of the most widely used and …

Hierarchically structured agent plans are important for efficient planning and acting, and they
also serve (among other things) to produce “richer” classical plans, composed not just of a …