Abstracts E-CAP2004

A Modal Perspective on Proof Dynamics Patrick Allo Core aim of this paper is to focus on the dynamics of real proofs by introducing the block-semantics from [Batens, 1995] as a dynamical counterpart for classical semantics. We first look briefly at its original formulation - with respect to natural deduction proofs - and then extend its use to tableau-proofs. This yields a perspective on proofdynamics that (i) explains proofs as a series of steps providing us with an insight in the premises, and (ii) reveals an informational dynamics in proofs unknown to most dynamical logical systems. As the latter remark especially applies to Amsterdamstyle dynamic epistemic logic, we consider a weak modal epistemic logic and combine it with dynamic modal operators expressing the informational proof-dynamics (as a natural companion for the informational dynamics due to new information known from dynamic epistemic logic). The motivation for this approach is twofold. In a general way it is considered as (a first step in) the reconstruction of the proofdynamics known from adaptive logics (revealed by its block-formulation) within a modal framework (i.e. using a relational structure); in a more restricted way it aims at the explicit application of some results on omniscience formulated in Batens’ paper on block-semantics. Coping with Meaning Towards an Evolutively Plausible Computational Semantics Asunción Álvarez One of the most common objections laid against the computational approach to the study of the mind is that it fails to take into account the evolutionary factors which have shaped the development of the cognitive system. In this paper, I will examine the possibility of providing a computational account which is also sound in Darwinian terms as regards the question of mental representation – that is, the relation between mental symbols and their meanings. Classical computational theories of mind have traditionally tended to resort to covariance and functionalist accounts of meaning in order to provide a semantics of mental states. I will argue however that a teleological evolutionary account of the meaning of mental symbols, such as the teleosemantics postulated by Ruth Millikan, would provide a more plausible naturalistic semantics, in particular when combined with a neural-networks model of mental processing. In the first part of the paper, I will give a brief summary of the classical computationalist account of mental processes, based on the Turing Machine model, and the functionalist semantics which it usually resorts to in order to explain the relationship of mental symbols to actual reality. I will also describe the Parallel Distributed Processing approach, which is modelled on neural networks and as such appears to be closer to biological and evolutionary reality than its alternative. In the second part, I will sketch out the outline of Millikan’s teleosemantics and its evolutionary background. Finally, in the third part, I will argue that the greater biological plausibility of the PDP model is reinforced when combined with a teleofunctional semantics, and discuss the advantages that such combination would have over traditional Turing-machine functionalism. The dynamic nature of meaning Claudia Arrighi and Roberta Ferrario The central issue of this paper is that of showing that there is not such a thing like the exact meaning of a word or expression, but meaning is something that gradually evolves from the dynamic processes of communication. Starting from this assumption, we present a draft of a theory whose aim is twofold: on the one hand, it describes how the meaning is formed as a mental state of individual agents (private meaning) and, on the other hand, it shows how a public meaning emerges from the interaction of agents. As a possibility to represent private meaning we take a flexible semantic network, where words (or concepts) are connected one another when they frequently present themselves together in the experience of the agent. Hence, when agents find themselves in a communicative situation, they start with different backgrounds and thus with different semantic networks to represent the private meaning they ascribe to a certain word or expression; in order to be able to understand each other, they need to agree on a public meaning that is then the result of a negotiation process. It is important to notice that these two “sides” of the matter are strongly interconnected, since not only the public meaning evolves as a compromise between different private meanings, but the private meanings are also continually reshaped by these intercourses. Our goal is to provide a viable philosophical approach for a dynamic definition of meaning. A multitude of works in this direction has been put forward by computer scientists dealing with problems of heterogeneity of sources of information. In fact, computer scientists are often in need of making different systems (that have their information stored and organized in totally different ways) communicate. Sometimes different systems just store the same information under different labels (names) or, vice versa, use the same label for different types of information; given all this, it should appear immediately evident why a better definition of meaning is so important even for computer science. This paper argues that a suitable solution for both disciplines could be reached by a more systematic characterization of the processes of meaning negotiation. 1 Intelligent Alarm Correlation and Abductive Reasoning Stefania Bandini, Alessandro Mosca and Matteo Palmonari The main aim of this paper is to present a way to improve the efficiency of an intelligent alarm correlation system (ACS) by means of an abductive reasoner. The ACS is integrated in a complex architecture (SAMOT) that performs monitoring and control tasks over tracts of highways. SAMOT's architecture consists of cameras for data acquisition, Video-Image Processors (VIPs - providing local interpretations of traffic anomalies), the knowledge-based alarm correlation module, and a control actions level. VIPs are able to detect many interesting anomalous situations concerning traffic flows and the correlation of alarms detected allows to provide a more global view of the system; nevertheless, there are useful information about traffic that are not provided neither by VIPs nor by the correlation of their outputs due to technological and efficiency constraints. On the basis of a specific theory on the domain explanations of anomalous traffic patterns can be provided taking into account those situations not directly detected by VIPs. The integration of the comprehensive view obtained by correlation with specific domain knowledge allows to abduce from the observed anomalous traffic patterns other significant situations. The experience of traffic operators allows to build a theory of abducible explanations that exploits the knowledge of the use context of the system. The abductive module can trigger the activation of proper further control actions, both automated and manual. Inferences previously draft may be kept or retracted after these further controls with a formal nonmonotonic mechanism very similar to usual human control activities. The paper will focus on the formal description of the abductive model. The correlation module of SAMOT has been modelled within a propositional modal formalism, named ST-Logic, which will be adopted for the abductive reasoner as well. Finally, some remarks about stratified interpretative cycles made possible within such a formal framework will be addressed. An argument against computationalism Eduard Barbu Computationalism claims that a system (human beings included) has cognitive states by implementing the right kind of computation. The centrality of computationalism in the study of cognition was forcefully challenged before by many authors. Nevertheless its position in cognitive science seems to be very solid. The argument against computationalism we will present is based on a well-known Putnam's argument against functionalism. Putnam's argument targets the functionalism in his implementation aspect. If we are allowed to consider arbitrary disjunction of physical states as realization of the formal states of an automaton, then we will obtain the result that any open physical system is implementing any finite state automaton (FSA). This leads to the equivalence between functionalism and behaviorism. We will start by exposing the motives that lead Putnam, many years ago, to advance the hypothesis the mental states are identical with functional states. After shortly introducing the notions that help us to understand Putnam's argument (FSA, maximal state, the principle of implementation, etc.) we will present the argument. The argument has two parts. In the first part Putnam proves that any open physical systems implements any inputless FSA. In the second part Putnam extends his result to FSA with input and output. We will accept the critique of Chalmers, namely that Putnam does not establish that every open physical system implements any FSA with input and output but a weaker result, that is any open physical system implements a trace of the execution of a FSA. We will show then that even this weaker result is sufficient to undermine functionalism, and implicitly computationalism. For this we will consider a human being performing a cognitive activity over a period of time. If this human being has cognitive states in virtue of implementing a computation, then according to the weaker form of Putnam's

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