An autonomous agent operating in a dynamical environment must be able to perform several "intelligent" tasks, such as learning about the environment, planning its actions and reasoning about the effects of the chosen actions. For this purpose, it is vital that the agent has a coherent, expressive, and well understood means of representing its knowledge about the world.
Traditionally, all knowledge about the dynamics of the modeled world has been represented in complex and detailed action descriptions. The first contribution of this thesis is the introduction of domain constraints in TAL, allowing a more modular representation of certain kinds of knowledge.
The second contribution is a systematic method of modeling different types of conflict handling that can arise in the context of concurrent actions. A new type of fluent, called influence, is introduced as a carrier from cause to actual effect. Domain constraints govern how influences interact with ordinary fluents. Conflicts can be modeled in a number of different ways depending on the nature of the interaction.
A fundamental property of many dynamical systems is that the effects of actions can occur with some delay. We discuss how delayed effects can be modeled in TAL using the mechanisms previously used for concurrent actions, and consider a range of possible interactions between the delayed effects of an action and later occurring actions.
In order to model larger and more complex domains, a sound modeling methodology is essential. We demonstrate how many ideas from the object-oriented paradigm can be used when reasoning about action and change. These ideas are used both to construct a framework for high level control objects and to illustrate how complex domains can be modeled in an elaboration tolerant manner.