Introduction to algorithms
A bottom-up mechanism for behavior selection in an artificial creature
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
The use of hierarchies for action selection
Adaptive Behavior
Planification versus sensory-motor conditioning: what are the issues?
Proceedings of the fifth international conference on simulation of adaptive behavior on From animals to animats 5
The program-size complexity of self-assembled squares (extended abstract)
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Stigmergy, self-organization, and sorting in collective robotics
Artificial Life
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Running time and program size for self-assembled squares
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
An Behavior-based Robotics
Learning Spatial and Temporal Correlation for Navigation in a 2-Dimensional Continuous World
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Cooperative multi-robot box-pushing
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
A Distributed Feedback Mechanism to Regulate Wall Construction by a Robotic Swarm
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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A behavior-based architecture (ConAg) with a connectionist action selection mechanism is introduced that enables a society of autonomous agents to construct arbitrary structures in their simulated two-dimensional world. Construction in this environment involves the agents picking up colored discs and dropping them at incomplete parts of the structure being built. The ConAg architecture provides both reactive behaviors which are used to maintain the viability of the agent and navigational planning behaviors that are used for construction. The action selection mechanism enables learning the sequence of behaviors required for construction by reinforcement learning. The navigational planning behaviors use a grid-based representation of the world. The shape of the structure to be built is also encoded on an internal spatial map. Path planning is implemented by spreading activations on sets of grid-based maps so that the agents perform the construction task efficiently. Construction of arbitrary structures is supported by temporal sequencing of goals. We present simulation results that demonstrate the performance of the architecture and algorithms.