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A rational agent exploring a complex and dynamic environment with incomplete information needs cognitive capabilities, e.g. planning, in addition to its perception and reaction for basic functionalities. However, mere planning, i.e., reasoning about sequences of actions, is not sufficient to solve problems in such complex environment. This is because (i) agents need to execute actions while they plan, (ii) they must gather and interpret sensor information, (iii) revise their world model, and (iv) adapt their own goals during a task.The knowledge representation and non monotonic reasoning area has shown the advantage of using logical formalisms to specify rational agents for complex robot applications, also called cognitive robotics applications. An example of such formalism is the Golog language and its different dialects. What those areas are still missing is implementational testbeds to evaluate existing theories. Since practical experimentation highlights the need for the improvement of existing formal theories at the ontological level. This work presents a logic-based implementation of an agent for the Wumpus World domain, which can be envisaged as a simplified model of an agent that reasons logically about its actions and sensor information in the presence of incomplete knowledge. Through a complete implementation of an agent in a real robot, the Lego R MindStorms TM robot, we show some experiments to verify that the Wumpus World can be an implementational testbed used to identify difficulties in transforming theory into operational solutions.

Social computers have been characterised as goal oriented complex systems comprised of humans as well as computational devices. Such systems can be found in natura in a variety of scenarios, as well as designed to tackle specific issues of social and economic relevance. In the present article we introduce the Lightweight Situated Social Calculus (LS 2 C) as a language to design executable specifications of interaction protocols for social computations. Additionally, we describe a platform to process these specifications, giving them a computational realisation. We argue that LS 2 C can be used to design, implement and execute social computations.

AS0"-PO BOX 20570-01498-070 "Reach what you cannot"Nikos KazantzakisIn this article we compare two well-known techniques for reasoning with uncertainty-namely, Incidence Calculus and Fagin-Halpern's version of the Theory of Evidence-from a viewpoint not so frequently explored for such techniques. We argue that, despite the equivalence relations that these techniques have been proved to hold, they have intrinsically different r8les as representations of uncertainty for automated reasoning, in the sense that the former represents approximations to uncertainty values due to impossibility to achieve exact results by proof-theoretic means, and the latter represents model-theoretic limits of definability of uncertainty values. 0 1995 John Wiley & Sons, Inc.