A number of protocols based on the formal dialogue games of philosophy have recently been proposed for interactions between autonomous agents. Several of these proposals purport to assist agents engaged in the same types of interactions, such as persuasions and negotiations, and are superficially different. How are we to determine whether or not these proposals are substantially different ? This paper considers this question and explores several alternative definitions of equivalence of protocols.

Dialogue protocols have been the subject of considerable attention with respect to their potential applications in multi-agent system environments. Formalisations of such protocols define classes of dialogue locutions, concepts of a dialogue state, and rules under which a dialogue proceeds. One important consideration in implementing a protocol concerns the criteria an agent should apply in choosing which utterance will constitute its next contribution to a discussion in progress: ideally, an agent should select a locution that (by some measure) "optimises" the outcome. The precise interpretation of `optimise' is, however, something that may vary greatly depending on the nature and intent of a dialogue area. Thus, in dialogue models of bidding and bargaining one widely studied concept of `optimality' is that each agent's selected locution affords a particular utility value to that agent, which is `maximal' in the sense that no agent can gain greater utility by unilaterally deviating from its choice. This concept of optimality, while suitable for scenarios such as bargaining, is, arguably, less appropriate for other areas. If we consider `persuasion' protocols, where one agent's intention is to convince others of the validity or invalidity of a specific proposition, then optimality might be better regarded in the sense of "choice of locution that results in a `minimal length' debate": thus the agent defending a hypothesis tries to select utterances that will convince other participants of the validity of this hypothesis after `as few locutions as possible'. We present a formal setting for considering the problem of deciding if a particular utterance in the context of a persuasion dialogue is optimal in this sense. We show that, in general, this decision problem is both N...

Dialogue protocols have been the subject of considerable attention with respect to their potential applications in multiagent system environments.

When is it okay to lie? And what constitutes a lie, anyway? This paper examines the notion of lying in agent-based systems, focusing on dialogues and situations where it is acceptable for agents to utter locutions that contradict their beliefs. We examine situations in human and animal behavior where lying --- acting or making statements that contradict one's set of beliefs --- is considered to be socially acceptable or even necessary for survival.

the data/case in question, whereas chance discovery applications typically have no such past data or similar cases upon which to draw. How do we forecast demand, for example, for an innovative new product ? We can ask potential consumers what they think of it, and whether or not they will buy it, but if they have no prior experience of the product or anything related their answers are likely to be misleading. Likewise, looking at demand for similar or substitute products may also mislead: it makes no sense to forecast the demand for a new bridge, for example, on the basis of the numbers of people who currently swim across the river it will span. This forecasting problem is accentuated if one person's utility from the innovation depends on its prior adoption by others, as is the case with many telecommunications products. Forecasts for terrestrial mobile telecommunications services, for instance, have consistently and greatly under-estimated the actual demand [4]. The task of demand for

This paper describes the development of a 3D laser scanner and an approach to 3D mapping and localization. The 3D scanner consists of a standard 2D laser scanner and a rotating mirror assembly. Employing multiple robots and mutual localization local 3D maps are built. Global localization within the maps is performed by extracting a cross-section of the map just below the ceiling and then using an exhaustive search algorithm to enable the merger of multiple local 3D maps. The quality of these maps is such that the poses estimated by this method are accurate to within 0.1m and 1 degree.

Autonomous agents within a multi-agent system can undertake behaviors that, while profitable for them, are damaging to the system as a whole. One way of regulating an agent's behavior is by obliging it to act in accordance with a set of specifications set out in a contract, and sanctioning it otherwise. In this

We consider a multi-agent system where each agent is equipped with a Bayesian network, and present an open framework for the agents to compromise on a possible consensus network. The framework builds on formal argumentation, and unlike previous solutions on graphical consensus belief, it is sufficiently general to allow for a wide range of compromises to be identified.

is it okay to lie? A simple model of contraditcion