Real-world applications of automated theorem proving require modern software environments that enable modularisation, networked inter-operability, robustness, and scalability. These requirements are met by the Agent-Oriented Programming paradigm of Distributed Artificial Intelligence. We argue that a reasonable framework for automated theorem proving in the large regards typical mathematical services as autonomous agents that provide internal functionality to the outside and that, in turn, are able to access a variety of existing external services. This article describes...

We introduce a resource adaptive agent mechanism which supports the user of an interactive theorem proving system. The mechanism, an extension of [4], uses a two layered architecture of agent societies to suggest applicable commands together with appropriate command argument instantiations. Experiments with this approach show that its effectiveness can be further improved by introducing a resource concept. In this paper we provide an abstract view on the overall mechanism, motivate the necessity of an appropriate resource concept and discuss its realization within the agent architecture.

. Hybrid agent architectures are particularly successful in implementing a broad spectrum of (sub-)cognitive abilities, such as reactive feedback, deliberative problem solving, and social coordination. They can be seen as special instances of boundedly rational systems, i.e., systems that trade off the quality of a decision vs the invested consumption of resources. For sophisticated domains, such as the virtual soccer environment of the RoboCup simulation, we argue that a generalised framework that combines a hybrid design with explicit resourceadapting mechanisms is reasonable. Based on the layered agent model InteRRaP, we describe an experimental setting that is to guide and to evaluate the development of reasoning about abstract resources. These are representations of general interdependencies between computational processes. 1 Introduction In the nineties, the complementary AI paradigms of deliberative, perfect rationality and of reactive, myopic emergence have found th...

We introduce a resource adaptive agent mechanism which supports the user in interactive theorem proving. The mechanism, an extension of [4], uses a two layered architecture of agent societies to suggest appropriate commands together with possible command argument instantiations. Experiments with this approach show that its effectiveness can be further improved by introducing a resource concept. In this paper we provide an abstract view on the overall mechanism, motivate the necessity of an appropriate resource concept and discuss its realization within the agent architecture. 1