Research based on children's performance on standard false-belief reasoning tasks indicates that theory of mind (ToM) understanding, (i.e. the ability to represent, conceptualize, and reason about one's own and others' mental states) is initially absent and develops around the age of four years (Wellman et al., 2001). Recently, researchers have investigated the relationship between language and ToM development. According to de Villiers & Pyers (2002) understanding of embedded complement structures is necessary for children to be able to understand false belief, because both require the ability to handle misrepresentation. Following Perner (1991), Smith et al. (2003) argued (contra De Villiers & Pyers) that the developmental link between embedded clauses and false belief reasoning skills stems instead from a requirement to handle metarepresentation. They proposed that children's aptitude with double-event relative clauses predicts their false-belief reasoning ability. Previous research on linguistic precursors of false belief understanding has focused largely on English speaking children. The current research hypothesized that crosslinguistic differences in the emergence of ToM understanding could result because of the potential for a developmental link between ToM understanding and other linguistic properties (e.g. scrambling), found in free word order languages, such as Russian. The current research sought to determine whether there is a correlation between the development of false belief reasoning skills and the acquisition of relativization in monolingual Russian speaking children; and to find out whether the acquisition of scrambled word orders (e.g. OVS) is a better predictor of false belief reasoning in child Russian. The participants of the study were 36 monolingual Russian children: 18 3-year-olds (Mean age = 3;6) and 18 4-year-olds (Mean Age= 4;6). We assessed the children's false belief understanding using the unexpected contents task and the unexpected transfer task and their ability to handle relative clauses and scrambled (OVS) word order through a Truth-Value judgment (TVJ) act-out task (Crain & Thornton, 1998). Our results confirm the previously established link between age and false belief reasoning. However, the results failed to support previous findings regarding the status of relative clauses as a linguistic precursor for the development of False Belief reasoning. The results also failed to confirm our predictions regarding the privileged role of scrambling (i.e. OVS sentences) in Russian children's ToM development. Our findings suggest that OVS sentences might be more difficult for Russian children to handle compared to relative clauses with the canonical SVO order, regardless of age the Russian children performed better on relative clauses than on scrambled OVS sentences -- this leads us to conclude -- "Syntax is easy! Pragmatics is hard!" Also there were no age related differences in relation to either relative clauses or scrambled word order sentences. Additionally, for child Russian, de Villiers & Peyers proposal regarding the privileged role of embedded complement clauses as a linguistic precursor to TOM development cannot yet be ruled out.

Psychological studies have shown that information exchange is a key component of effective teamwork. In addition to requesting information that they need for their tasks, members of effective teams often proactively forward information that they believe other teammates require to complete their tasks. We refer to this type of communication as proactive information exchange and the formalization and implementation of this is the subject of this thesis. The important question that we are trying to answer is: under normative conditions, what types of information needs can agent teammates extract from shared plans and how can they use these information needs to proactively forward information to teammates? In the following, we make two key claims about proactive information exchange: first, agents need to be aware of the information needs of their teammates and that these information needs can be inferred from shared plans; second, agents need to be able to model the beliefs of others in order to deliver this information efficiently. To demonstrate this, we have developed an algorithm named PIEX, which, for each agent on a team, reasonably approximates the information-needs of other team members, based on analysis of a shared team plan. This algorithm transforms a team plan into an individual plan by inserting coomunicative tasks in agents' individual plans to deliver information to those agents who need it. We will incorporate a previously developed architecture for multi-agent belief reasoning. In addition to this algorithm for proactive information exchange, we have developed a formal framework to both describe scenarios in which proactive information exchange takes place and to evaluate the quality of the communication events that agents running the PIEX algorithm generate. The contributions of this work are a formal and implemented algorithm for information exchange for maintaining a shared mental model and a framework for evaluating domains in which this type of information exchange is useful.

Psychological studies have shown that information exchange is a key component of effective teamwork. In addition to requesting information that they need for their tasks, members of effective teams often proactively forward information that they believe other teammates require to complete their tasks. We refer to this type of communication as proactive information exchange and the formalization and implementation of this is the subject of this thesis. The important question that we are trying to answer is: under normative conditions, what types of information needs can agent teammates extract from shared plans and how can they use these information needs to proactively forward information to teammates? In the following, we make two key claims about proactive information exchange: first, agents need to be aware of the information needs of their teammates and that these information needs can be inferred from shared plans; second, agents need to be able to model the beliefs of others in order to deliver this information efficiently. To demonstrate this, we have developed an algorithm named PIEX, which, for each agent on a team, reasonably approximates the information-needs of other team members, based on analysis of a shared team plan. This algorithm transforms a team plan into an individual plan by inserting coomunicative tasks in agents' individual plans to deliver information to those agents who need it. We will incorporate a previously developed architecture for multi-agent belief reasoning. In addition to this algorithm for proactive information exchange, we have developed a formal framework to both describe scenarios in which proactive information exchange takes place and to evaluate the quality of the communication events that agents running the PIEX algorithm generate. The contributions of this work are a formal and implemented algorithm for information exchange for maintaining a shared mental model and a framework for evaluating domains in which this type of information exchange is useful.

Dans le domaine de la modélisation du raisonnement, plusieurs approches se basent sur les logiques modales qui permettent de formaliser le raisonnement sur des éléments non factuels, comme la croyance, le savoir ou encore la nécessité. Une extension pondérées de ces logiques modales permet de moduler les éléments non factuels qu'elle décrit. En particulier, nous nous intéressons à l'extension pondérée des logiques modales qui permet de formaliser des croyances graduelles : nous traitons des aspects sémantiques et axiomatiques ainsi que des aspects syntaxiques liés à la manipulations de telles croyances modulées. Ainsi, les travaux de cette thèse sont organisés en trois parties. Nous proposons, d'une part, une sémantique proportionnelle qui étend la sémantique de Kripke classiquement utilisée pour les logiques modales ; ainsi qu'une étude des axiomes modaux dans le contexte de cette sémantique des modalités pondérées. D'autre part, nous proposons un modèle ensembliste flou pour représenter et manipuler des degrés de croyances. Enfin, nous mettons en œuvre ces modèles théoriques dans deux applications : un outil de vérification de formules modales pondérées et un joueur artificiel pour le jeu coopératif Hanabi dont la prise de décision repose sur un raisonnement sur ses propres croyances. / In the field of reasoning models, many approaches are based on modal logics, which allow to formalise the non-factual reasoning, as belief, knowledge or necessity reasoning. A weighted extension for these modal logics aims at modulating the considered non-factual elements. In particular, we examine the weighted extension of modal logics for graded beliefs: we study their semantical and axiomatical issues related to manipulating such modulated beliefs. Therefore, this thesis works are organised in three parts. We first propose a proportional semantics which extends the Kripke semantics, classically used for modal logics. We also study modal axioms regarding the proposed semantics. Then, we propose a fuzzy set model for representing and manipulating belief degrees. We finally use these two formal models in two different applications: a model checking tool for weighted modal formulae and an artifical player for a cooperative game called Hanabi in which decision making is based on graded belief reasoning.