Making sense of actor behaviour: an algebraic filmstrip pattern and its implementation

Sense-making with respect to actor-based systems is challenging because of the non-determinism arising from concurrent behaviour. One strategy is to produce a trace of event histories that can be processed post-execution. Given a semantic domain, the histories can be translated into visual representations of the semantics in the form of filmstrips. This paper proposes a general pattern for the production of filmstrips from actor histories that can be implemented in a way that is independent of the particular data types used to represent the events, semantics and graphical displays. We demonstrate the pattern with respect to a simulation involving predators and prey which is a typical agent-based application

Making sense of actor behaviour: an algebraic filmstrip pattern and its implementation

Sense-making with respect to actor-based systems is challenging because of the non-determinism arising from concurrent behaviour. One strategy is to produce a trace of event histories that can be processed post-execution. Given a semantic domain, the histories can be translated into visual representations of the semantics in the form of filmstrips. This paper proposes a general pattern for the production of filmstrips from actor histories that can be implemented in a way that is independent of the particular data types used to represent the events, semantics and graphical displays. We demonstrate the pattern with respect to a simulation involving predators and prey which is a typical agent-based application

Designing a source-level debugger for cognitive agent programs

When an agent program exhibits unexpected behaviour, a developer needs to locate the fault by debugging the agent’s source code. The process of fault localisation requires an understanding of how code relates to the observed agent behaviour. The main aim of this paper is to design a source-level debugger that supports single-step execution of a cognitive agent program. Cognitive agents execute a decision cycle in which they process events and derive a choice of action from their beliefs and goals. Current state-of-the-art debuggers for agent programs provide insight in how agent behaviour originates from this cycle but less so in how it relates to the program code. As relating source code to generated behaviour is an important part of the debugging task, arguably, a developer also needs to be able to suspend an agent program on code locations. We propose a design approach for single-step execution of agent programs that supports both code-based as well as cycle-based suspension of an agent program. This approach results in a concrete stepping diagram ready for implementation and is illustrated by a diagram for both the Goal and Jason agent programming languages, and a corresponding full implementation of a source-level debugger for Goal in the Eclipse development environment. The evaluation that was performed based on this implementation shows that agent programmers prefer a source-level debugger over a purely cycle-based debugger.Interactive Intelligenc