Advances in evolutionary computing
Curious agents and situated design evaluations
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Modeling motivation for adaptive nonplayer characters in dynamic computer game worlds
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Anticipatory Behavior in Adaptive Learning Systems
DS'07 Proceedings of the 10th international conference on Discovery science
Towards directed open-ended search by a novelty guided evolution strategy
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Intrinsically motivated intelligent rooms
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Novelty and interestingness measures for design-space exploration
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Interestingness depends on the observer''s current knowledge and computational abilities. Things are boring if either too much or too little is known about them --- if they appear either trivial or random. Interesting are unexpected regularities that seem easy to figure out. I attempt to implement these ideas in a ``curious'''', ``creative'''' explorer with two co-evolving ``brains''''. It executes a lifelong sequence of instructions whose modifiable probabilities are conditioned on both brains --- both must {\em agree} on each instruction. There are special instructions for comparing computational results. The brains can predict outcomes of such comparisons. If their opinions differ, then the winner will get rewarded, the loser punished. Hence each brain wants to lure the other into agreeing upon instruction subsequences involving comparisons that surprise it. The surprised brain adapts. In turn, the other loses a source of reward --- an incentive to shift the focus of interest. Both brains deal with the complex credit assignment problem using the recent Incremental Self-Improvement paradigm. Extensive simulations include an example where curiosity helps to speed up external reward.