The TROCA Project: An autonomous transportation robot controlled by a cognitive architecture

Autonomous mobile robots emerged as an important kind of transportation system in warehouses and factories. In this work, we present the use of MECA cognitive architecture in the development of an artificial mind for an autonomous robot responsible for multiple tasks, including transportation of packages along a factory floor, environment exploration, warehouse inventory, its internal energy management, self-monitoring and dealing with human operators and other robots. The present text provides a detailed specification for the architecture and its software implementation. Future work will present the simulation results under different configurations, together with a detailed analysis of the architecture performance and its generalization for autonomous robot control.     

Representing decision-makers using styles of behavior: An approach designed for group decision support systems

Supporting decision-making processes when the elements of a group are geographically dispersed and on a tight schedule is a complex task. Aiming to support decision-makers anytime and anywhere, Web-based group decision support systems have been studied. However, the limitations in the decision-makers’ interactions associated to this scenario bring new challenges. In this work, we propose a set of behavioral styles from which decision-makers’ intentions can be modelled into agents. The goal is that, besides having agents represent typical preferences of the decision-makers (towards alternatives and criteria), they can also represent their intentions. To do so, we conducted a survey with 64 participants in order to find homogeneous operating values so as to numerically define the proposed behavioral styles in four dimensions. In addition, we also propose a communication model that simulates the dialogues made by decision-makers in face-to-face meetings. We developed a prototype to simulate decision scenarios and found that agents are capable of acting according to the decision-makers’ intentions and fundamentally benefit from different possible behavioral styles, just as a face-to-face meeting benefits from the heterogeneity of its participants.     

Thought-shape fusion in anorexia nervosa: an experimental investigation

Cognitive biases and cognitive distortions have been implicated as important factors in the development and maintenance of many disorders. The concept of thought-shape fusion (TSF) in eating disorders was developed by Shafran, Teachman, Kerry, and Rachman (British Journal of Clinical Psychology 38 (1999) 167) as a variant of thought-action fusion, described by Shafran, Thordarson and Rachman (Journal of Anxiety Disorders 10 (1996) 379). TSF occurs when thinking about eating certain types of food increases a person's estimate of their shape and/or weight, elicits a perception of moral wrongdoing, and/or makes the person feel fat. Shafran et al. (1999) examined both the psychometric and experimental properties of TSF in an undergraduate sample. This paper reports an extension of this work to a clinical group (N=20) of patients with anorexia nervosa. After completing a set of relevant questionnaires, participants were asked to think about a food which they considered extremely fattening. They were then asked to write out the sentence, "I am eating--.", inserting the name of the fattening food in the blank. After being asked to rate their anxiety, guilt, feelings about their weight, morality, etc., participants were given the opportunity to neutralize their statement in any way they chose. The majority of the participants neutralized in ways consistent with the findings of Shafran et al. (1999). The results are discussed in terms of cognitive-behavioural formulations of eating disorders, and of the influence of cognitive biases and cognitive distortions on the processing of information relevant to food, weight and shape in anorexia nervosa.     

Rich interpretation vs. deflationary accounts in cognitive development: the case of means-end skills in 7-month-old infants

Seven-month-old infants appear to learn means-end skills, such as pushing a button to retrieve a distant toy (Psychological Review 104 (1997) 686). The present studies tested whether such apparent means-end behaviors are genuine, or simply the repetition of trained behaviors under conditions of greatest arousal, as suggested by a dynamic systems reinterpretation. When infants were trained to repeat behaviors that did not serve as means to retrieving toys (pushing a button to light a set of distant lights), their button-pushing differed significantly from infants for whom button-pushing served as a means for retrieving toys. Further, infants demonstrated means-end skills with behaviors that they had not been trained to repeat. Implications for early means-end abilities and for debates surrounding the interpretation of infant behavior are discussed.     

Treating a Chronically Depressed Adolescent Female Using the Cognitive Behavioral Analysis System of Psychotherapy: A Case Study

A case is presented of an adolescent female with double depression who was treated using the Cognitive Behavioral Analysis System of Psychotherapy (CBASP). CBASP is designed to teach a social problem-solving procedure called Situational Analysis (SA). Generalized treatment effects were measured through monitoring of diagnostic status, two administrations of the Minnesota Multiphasic Personality Inventory-Adolescent, weekly administrations of the Child Depression Inventory, and acquisition performance ratings on the SA task. The results showed that CBASP appeared to be an effective treatment. The double depressive disorder remitted, and the patient learned to identify behavioral consequences as well as target and attain her interpersonal goals. CBASP can be effective for adolescents, although modifications of the adult form of the therapy may be necessary.     

Entailment with Near Surety of Scaled Assertions of High Conditional Probability

An assertion of high conditional probability or, more briefly, an HCP assertion is a statement of the type: The conditional probability of B given A is close to one. The goal of this paper is to construct logics of HCP assertions whose conclusions are highly likely to be correct rather than certain to be correct. Such logics would allow useful conclusions to be drawn when the premises are not strong enough to allow conclusions to be reached with certainty. This goal is achieved by taking Adams" (1966) logic, changing its intended application from conditionals to HCP assertions, and then weakening its criterion for entailment. According to the weakened entailment criterion, called the Criterion of Near Surety and which may be loosely interpreted as a Bayesian criterion, a conclusion is entailed if and only if nearly every model of the premises is a model of the conclusion. The resulting logic, called NSL, is nonmonotonic. Entailment in this logic, although not as strict as entailment in Adams" logic, is more strict than entailment in the propositional logic of material conditionals. Next, NSL was modified by requiring that each HCP assertion be scaled; this means that to each HCP assertion was associated a bound on the deviation from 1 of the conditional probability that is the subject of the assertion. Scaling of HCP assertions is useful for breaking entailment deadlocks. For example, it it is known that the conditional probabilities of C given A and of ¬ C given B are both close to one but the bound on the former"s deviation from 1 is much smaller than the latter"s, then it may be concluded that in all likelihood the conditional probability of C given A B is close to one. The resulting logic, called NSL-S, is also nonmonotonic. Despite great differences in their definitions of entailment, entailment in NSL is equivalent to Lehmann and Magidor"s rational closure and, disregarding minor differences concerning which premise sets are considered consistent, entailment in NSL-S is equivalent to entailment in Goldszmidt and Pearl"s System-Z ⁺. Bacchus, Grove, Halpern, and Koller proposed two methods of developing a predicate calculus based on the Criterion of Near Surety. In their random-structures method, which assumed a prior distribution similar to that of NSL, it appears possible to define an entailment relation equivalent to that of NSL. In their random-worlds method, which assumed a prior distribution dramatically different from that of NSL, it is known that the entailment relation is different from that of NSL.