Integration of psychological models in the design of artificial creatures

Artificial creatures form an increasingly important component of interactive computer games. Examples of such creatures exist which can interact with each other and the game player and learn from their experiences. However, we argue, the design of the underlying architecture and algorithms has to a large extent overlooked knowledge from psychology and cognitive sciences. We explore the integration of observations from studies of motivational systems and emotional behaviour into the design of artificial creatures. An initial implementation of our ideas using the “sim agent” toolkit illustrates that physiological models can be used as the basis for creatures with animal like behaviour attributes. The current aim of this research is to increase the “realism” of artificial creatures in interactive game-play, but it may have wider implications for the development of AI

Generación de expresiones faciales basadas en emociones para criaturas virtuales

En este trabajo de investigaci on se estudian los comportamientos humanos, específicamente las expresiones faciales, ya que estas son un aspecto fundamental en las emociones que genera el ser humano al poder discutir si podemos o no expresar en el rostro algo que no sea una emoci on. En el contenido de esta tesis se introducen algunos conceptos b asicos de la Inteligencia Arti cial, como agentes inteligentes, la computaci on bio-inspirada, entre otros, para lograr que una criatura virtual represente 5 emociones b asicas (alegr a, tristeza, miedo, enojo y desagrado) en su rostro, la generaci on de estas emociones son detonadas mediante est mulos que se encuentran en un ambiente virtual y a la vez mostradas en una expresi on facial. De esta manera la propuesta que se hace en esta tesis es modelar una criatura virtual embebiendo en ella una base de conocimiento inicial generada con base en Neurociencias y generar est mulos con diversas caracter sticas, tomando como caso de estudio los coloresque est an relacionados a las emociones b asicas, para desp ues introducir a la criatura virtual y a los est mulos de manera que estos ultimos exciten a la criatura virtual y esta pueda generar la expresi on facial de acuerdo a su base de conocmiento inicial, lo que permite mostrar un comportamiento que se asemeje un poco m as al que tendr a una persona real

The future of the moving image

Whilst at the Universities of Bristol and the West of England, in collaboration with BBC R&D, I have been responsible for the production of the first higher dynamic range, higher resolution and higher frame rate experiments to measure which combination of these developing parameters of image capture and display best engages the audience. What is essentially happening here is the mapping of the capabilities of imagining equipment to the sensory levels of the eye/brain pathway. But what do the expanding parameters of the digitally captured moving image mean to the viewer and how will this affect future patterns of production, consumption and understanding of moving images

Action in Mind: Neural Models for Action and Intention Perception

To notice, recognize, and ultimately perceive the others’ actions and to discern the intention behind those observed actions is an essential skill for social communications and improves markedly the chances of survival. Encountering dangerous behavior, for instance, from a person or an animal requires an immediate and suitable reaction. In addition, as social creatures, we need to perceive, interpret, and judge correctly the other individual’s actions as a fundamental skill for our social life. In other words, our survival and success in adaptive social behavior and nonverbal communication depends heavily on our ability to thrive in complex social situations. However, it has been shown that humans spontaneously can decode animacy and social interactions even from strongly impoverished stimuli and this is a fundamental part of human experience that develops early in infancy and is shared with other primates. In addition, it is well established that perceptual and motor representations of actions are tightly coupled and both share common mechanisms. This coupling between action perception and action execution plays a critical role in action understanding as postulated in various studies and they are potentially important for our social cognition. This interaction likely is mediated by action-selective neurons in the superior temporal sulcus (STS), premotor and parietal cortex. STS and TPJ have been identified also as coarse neural substrate for the processing of social interactions stimuli. Despite this localization, the underlying exact neural circuits of this processing remain unclear. The aim of this thesis is to understand the neural mechanisms behind the action perception coupling and to investigate further how human brain perceive different classes of social interactions. To achieve this goal, first we introduce a neural model that provides a unifying account for multiple experiments on the interaction between action execution and action perception. The model reproduces correctly the interactions between action observation and execution in several experiments and provides a link towards electrophysiological detailed models of relevant circuits. This model might thus provide a starting point for the detailed quantitative investigation how motor plans interact with perceptual action representations at the level of single-cell mechanisms. Second we present a simple neural model that reproduces some of the key observations in psychophysical experiments about the perception of animacy and social interactions from stimuli. Even in its simple form the model proves that animacy and social interaction judgments partly might be derived by very elementary operations in hierarchical neural vision systems, without a need of sophisticated or accurate probabilistic inference

A Theoretical Cognitive Construct of a 3D Embodied Agent: VAL, the Virtual Autonomous Learner

The cognitive sciences have always educated educators by providing a pedagogical framework as a guide. However, the standard cognitive sciences are being challenged by a new paradigm, embodied cognition, in which learning is part of a dynamical system. In this paradigm, virtual embodiment (VE) is the new artificial intelligence (AI). This thesis is an application of VE, introducing an approach to developing a virtual 3D agent that has the potential to achieve “strong AI” status. I believe such agents can mature into AI educators. And that the development of a great AI educator starts with the development of a humble AI child. My methodological approach is a metasynthesis of a broad range of disciplines and consists of (1) the use of empirical research to ground my ideas, (2) the integration of dissimilar research to construct new ideas, and (3) the use of thought experiments to uncover the fundamental nature of learning within an embodiment paradigm. As a result, this thesis introduces a virtual 3D agent, the virtual autonomous learner (VAL), along with key elements of its ecological construct. With an embodied cognitive perspective, VAL seeks to find its own affordance and that of its environment. I conclude that (1) the construct for VAL needs to accommodate different cognitive architectures if we are to make full use of its methodology; (2) a rigorous virtual curriculum must be developed, and efficient pedagogical tools should be designed and developed to implement this curriculum; and (3) an educational perspective is paramount for this project

The enactive approach to architectural experience: A neurophysiological perspective on embodiment, motivation, and affordances

From the enactivist perspective, the way people perceptually experience the world, including architectural spaces, is governed by the dynamic sensorimotor activity of the human organism as a whole and is thereby influenced by the particular conditions of man’s embodiment

Virtual humans: thirty years of research, what next?

In this paper, we present research results and future challenges in creating realistic and believable Virtual Humans. To realize these modeling goals, real-time realistic representation is essential, but we also need interactive and perceptive Virtual Humans to populate the Virtual Worlds. Three levels of modeling should be considered to create these believable Virtual Humans: 1) realistic appearance modeling, 2) realistic, smooth and flexible motion modeling, and 3) realistic high-level behaviors modeling. At first, the issues of creating virtual humans with better skeleton and realistic deformable bodies are illustrated. To give a level of believable behavior, challenges are laid on generating on the fly flexible motion and complex behaviours of Virtual Humans inside their environments using a realistic perception of the environment. Interactivity and group behaviours are also important parameters to create believable Virtual Humans which have challenges in creating believable relationship between real and virtual humans based on emotion and personality, and simulating realistic and believable behaviors of groups and crowds. Finally, issues in generating realistic virtual clothed and haired people are presente

Intelligent Space environment for ethorobotics

This paper presents a setup using a mobile robot agent in an intelligent space. The proposed concept based on a holonomic driving system mount on the robot. Due to the driving system different moving behaviours and path planning algorithms can be tested. To examine the robot movements and provide the needed support the robot agent was placed in a Motion capture system. The special environment around the robot is a motion track system which can track the movements of agents in its space via markers