Objectives
Anticipatory behavior is a mechanism, or a behavior, that does not only depend on the past and present but also on predictions, expectations, or beliefs about the future.
The aim of this workshop is to bring together researchers that are interested in such anticipatory mechanisms and essentially anticipatory adaptive behavior. It is aimed for an interdisciplinary gathering that brings together researchers from various research areas including neuroscience, machine learning, artificial intelligence, control, vision research, and cognitive psychology so as to discuss and evaluate the different influences that predictions, expectations, goals, desires, or intentions can have on actual behavior, including influences on attention, action decision making and control, as well as learning.
After two previous successful gatherings during SAB 2002, resulting in the Springer-Verlag LNCS 2684 State-of-the-Art survey named after the workshop, and during SAB2004, ABiALS 2006 will build on the gathered insights and continue to explore anticipatory influences on behavior and learning.
Previous work on anticipatory behavior has concentrated more on the learning of models of environments, actuators, and environment dynamics. Up to now though, exploitation of the model has been done mainly to show that exploitation is possible or that an appropriate model exists in the first place. Only very few applications exist that show the utility of the model for the simulation of anticipatory processes and consequent adaptive behavior. However, the exploitation of the model and the interaction of learning and behavior by the means of the model is the most promising and important area for future research.
Essential Questions
- How can anticipations be exploited to guide and improve decision making and control?
- What is the trade-off between simple bottom-up stimulus-response driven behavior and more top-down anticipatory driven behavior?
- How can anticipations be exploited to direct or speed-up motor learning?
- How can anticipations influence further model learning?
- How can predictions be combined with consequent sensory input to improve, guide, and speed-up sensory processing?
- How can anticipations influence attention?
- How can such anticipatory mechanisms be implemented or integrated in an artificial learning system?
- What is the most suitable predictive representation to spark anticipatory behavior?
- How does an incomplete predictive model influence anticipatory behavior?
- Which anticipatory mechanisms can be distinguished? Which are the benefits/drawbacks of the different mechanisms?
- Which social agent interactions can be improved by the means of anticipatory behavior?
- What role do anticipations play for the implementation of motivations and emotions?
- How did different anticipatory capabilities emerge on the basis of previously existing cognitive capabilities in the course of evolution?
- Which animal species possess the various anticipatory capabilities?
- Where and how are anticipatory capabilities implemented in actual brains?
- Which specific roles do brain structures such as the cerebellum and prefrontal cortex play in anticipation?
- Which data from psychology can be addressed with the currently available anticipatory models?