14,733 research outputs found
Towards A Theory-Of-Mind-Inspired Generic Decision-Making Framework
Simulation is widely used to make model-based predictions, but few approaches
have attempted this technique in dynamic physical environments of medium to
high complexity or in general contexts. After an introduction to the cognitive
science concepts from which this work is inspired and the current development
in the use of simulation as a decision-making technique, we propose a generic
framework based on theory of mind, which allows an agent to reason and perform
actions using multiple simulations of automatically created or externally
inputted models of the perceived environment. A description of a partial
implementation is given, which aims to solve a popular game within the
IJCAI2013 AIBirds contest. Results of our approach are presented, in comparison
with the competition benchmark. Finally, future developments regarding the
framework are discussed.Comment: 7 pages, 5 figures, IJCAI 2013 Symposium on AI in Angry Bird
THE IMAGINATIVE REHEARSAL MODEL – DEWEY, EMBODIED SIMULATION, AND THE NARRATIVE HYPOTHESIS
In this contribution I outline some ideas on what the pragmatist model of habit ontology could offer us as regards the appreciation of the constitutive role that imagery plays for social action and cognition. Accordingly, a Deweyan understanding of habit would allow for an understanding of imagery in terms of embodied cognition rather than in representational terms. I first underline the motor character of imagery, and the role its embodiment in habit plays for the anticipation of action. Secondly, I reconstruct Dewey's notion of imaginative rehearsal in light of contemporary, competing models of intersubjectivity such as embodied simulation theory and the narrative practice hypothesis, and argue that the Deweyan model offers us a more encompassing framework which can be useful for reconciling these approaches. In this text I am mainly concerned with sketching a broad picture of the lines along which such a project could be developed. For this reason not all questions are given equal attention, and I shall concentrate mainly on the basic ideas, without going directly into the details of many of them
Effects of Anticipation in Individually Motivated Behaviour on Control and Survival in a Multi-Agent Scenario with Resource Constraints
This is an open access article distributed under the Creative Commons Attribution License CC BY 3.0 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Self-organization and survival are inextricably bound to an agent’s ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent’s peers in the anticipation process affect subjective control and survival strategies. To quantify control and drive behaviour, we use the recently developed information-theoretic quantity of empowerment with the principle of empowerment maximization. In two experiments involving extensive simulations, we show that agents develop risk-seeking, risk-averse and mixed strategies, which correspond to greedy, parsimonious and mixed behaviour. Although the principle of empowerment maximization is highly generic, the emerging strategies are consistent with what one would expect from rational individuals with dedicated utility models. Our results support empowerment maximization as a universal drive for guided self-organization in collective agent systemsPeer reviewedFinal Published versio
Intrinsic Motivation Systems for Autonomous Mental Development
Exploratory activities seem to be intrinsically rewarding
for children and crucial for their cognitive development.
Can a machine be endowed with such an intrinsic motivation
system? This is the question we study in this paper, presenting a number of computational systems that try to capture this drive towards novel or curious situations. After discussing related research coming from developmental psychology, neuroscience, developmental robotics, and active learning, this paper presents the mechanism of Intelligent Adaptive Curiosity, an intrinsic motivation system which pushes a robot towards situations in which it maximizes its learning progress. This drive makes the robot focus on situations which are neither too predictable nor too unpredictable, thus permitting autonomous mental development.The complexity of the robot’s activities autonomously increases and complex developmental sequences self-organize without being constructed in a supervised manner. Two experiments are presented illustrating the stage-like organization emerging with this mechanism. In one of them, a physical robot is placed on a baby play mat with objects that it can learn to manipulate. Experimental results show that the robot first spends time in situations
which are easy to learn, then shifts its attention progressively to situations of increasing difficulty, avoiding situations in which nothing can be learned. Finally, these various results are discussed in relation to more complex forms of behavioral organization and data coming from developmental psychology.
Key words: Active learning, autonomy, behavior, complexity,
curiosity, development, developmental trajectory, epigenetic
robotics, intrinsic motivation, learning, reinforcement learning,
values
Psychological Aspects of Market Crashes
This paper analyzes the sensitivity of market crashes to investors'psychology in a standard general equilibrium framwork. Contrary to the traditional view that market crashes are driven by large drops in aggregate endowments, we argue from a theoretical standpoint that individual anticipations of such drops are a necessary condition for crashes to occur, and that the magnitude or such crashes are poritively correlated with the level of individual anticipations of drops
Can Intellectual Processes in the Sciences Also Be Simulated? The Anticipation and Visualization of Possible Future States
Socio-cognitive action reproduces and changes both social and cognitive
structures. The analytical distinction between these dimensions of structure
provides us with richer models of scientific development. In this study, I
assume that (i) social structures organize expectations into belief structures
that can be attributed to individuals and communities; (ii) expectations are
specified in scholarly literature; and (iii) intellectually the sciences
(disciplines, specialties) tend to self-organize as systems of rationalized
expectations. Whereas social organizations remain localized, academic writings
can circulate, and expectations can be stabilized and globalized using
symbolically generalized codes of communication. The intellectual
restructuring, however, remains latent as a second-order dynamics that can be
accessed by participants only reflexively. Yet, the emerging "horizons of
meaning" provide feedback to the historically developing organizations by
constraining the possible future states as boundary conditions. I propose to
model these possible future states using incursive and hyper-incursive
equations from the computation of anticipatory systems. Simulations of these
equations enable us to visualize the couplings among the historical--i.e.,
recursive--progression of social structures along trajectories, the
evolutionary--i.e., hyper-incursive--development of systems of expectations at
the regime level, and the incursive instantiations of expectations in actions,
organizations, and texts.Comment: accepted for publication in Scientometrics (June 2015
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