New research on the adaptive behavior of natural and synthetic agents.

This book constitutes the proceedings of the 12th International Conference on Simulation of Adaptive Behaviour, SAB 2012, held in Odense, Denmark, in August 2012. The 22 full papers as well as 22 poster papers included in this volume were carefully reviewed and selected from 66 submissions. They are organized in topical sections named: animat approach and methodology; perception and motor control; evolution; learning and adaptation, and collective and social behaviour.

This book constitutes the proceedings of the 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, held in Aberystwyth, UK, in August 2016. The 31 papers presented in this volume were carefully reviewed and selected from 45 submissions. They cover the main areas in animat research, including the animat approach and methodology, perception and motor control, learning and adaptation, evolution, and collective and social behavior.

August 8-12, 1994, Brighton, England From Animals to Animats 3 brings together research intended to advance the fron tier of an exciting new approach to understanding intelligence. The contributors represent a broad range of interests from artificial intelligence and robotics to ethology and the neurosciences. Unifying these approaches is the notion of "animat" -- an artificial animal, either simulated by a computer or embodied in a robot, which must survive and adapt in progressively more challenging environments. The 58 contributions focus particularly on well-defined models, computer simulations, and built robots in order to help characterize and compare various principles and architectures capable of inducing adaptive behavior in real or artificial animals. Topics include: - Individual and collective behavior. - Neural correlates of behavior. - Perception and motor control. - Motivation and emotion. - Action selection and behavioral sequences. - Ontogeny, learning, and evolution. - Internal world models and cognitive processes. - Applied adaptive behavior. - Autonomous robots. - Heirarchical and parallel organizations. - Emergent structures and behaviors. - Problem solving and planning. - Goal-directed behavior. - Neural networks and evolutionary computation. - Characterization of environments. A Bradford Book

The Animals to Animats Conference brings together researchers fromethology, psychology, ecology, artificial intelligence, artificiallife, robotics, engineering, and related fields to furtherunderstanding of the behaviors and underlying mechanisms that allownatural and synthetic agents (animats) to adapt and survive inuncertain environments The Animals to Animats Conference brings together researchers from ethology, psychology, ecology, artificial intelligence, artificial life, robotics, engineering, and related fields to further understanding of the behaviors and underlying mechanisms that allow natural and synthetic agents (animats) to adapt and survive in uncertain environments. The work presented focuses on well-defined models--robotic, computer-simulation, and mathematical--that help to characterize and compare various organizational principles or architectures underlying adaptive behavior in both natural animals and animats.

From Animals to Animats 4 brings together the latest research at the frontier of an exciting new approach to understanding intelligence.

Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior

This book examines how two distinct strands of research on autonomous robots, evolutionary robotics and humanoid robot research, are converging. The book will be valuable for researchers and postgraduate students working in the areas of evolutionary robotics and bio-inspired computing.

As has been pointed out by several industrial game AI developers the lack of behavioral modularity across games and in-game tasks is detrimental for the development of high quality AI [605, 171]. An increasingly popular method for ad-hoc behavior authoring that eliminates the modularity limitations of FSMs and BTs is the utility-based AI approach which can be used for the design of control and decision making systems in games [425, 557]. Following this approach, instances in the game get assigned a particular utility function that gives a value for the importance of the particular instance [10, 169]. For instance, the importance of an enemy being present at a particular distance or the importance of an agent’s health being low in this particular context. Given the set of all utilities available to an agent and all the options it has, utility-based AI decides which is the most important option it should consider at this moment [426]. The utility-based approach is grounded in the utility theory of economics and is based on utility function design. The approach is similar to the design of membership functions in a fuzzy set. A utility can measure anything from observable objective data (e.g., enemy health) to subjective notions such as emotions, mood and threat. The various utilities about possible actions or decisions can be aggregated into linear or non-linear formulas and guide the agent to take decisions based on the aggregated utility. The utility values can be checked every n frames of the game. So while FSMs and BTs would examine one decision at a time, utility-based AI architectures

This book constitutes the thoroughly refereed joint post-proceedings of the 17th and 18th annual conferences of the Japanese Society for Artificial Intelligence, JSAI 2003 and JSAI 2004, and co-located international workshops, held in Niigata, Japan in June 2003 and in Kanazawa, Japan in May/June 2004 respectively. It features a number of award winning papers as well as revised full workshop papers from these conferences.