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A message-passing algorithm for multi-agent trajectory planning
A novel approach for computing collision-free global trajectories for p agents with specified initial and final configurations, based on an improved version of the alternating direction method of multipliers (ADMM), which allows for incorporating different cost functionals with only minor adjustments.
The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning
We describe a new instance-based learning algorithm called the Boundary Forest (BF) algorithm, that can be used for supervised and unsupervised learning. The algorithm builds a forest of trees whose
Extending soar with dissociated symbolic memories
A memory-centric analysis of Soar 9 is developed, a general cognitive architecture that incorporates multiple long-term memories that explores the functional abilities, computational opportunities, and theoretical challenges entailed by integrating a diverse set of symbolic memory systems.
Exploring Reinforcement Learning for Mobile Percussive Collaboration
This work addresses multiple challenges involved in the deployment of machine-learning algorithms for mobile music expression, including tradeoffs between learning speed & quality; interface design for human collaborators; and real-time performance and improvisation.
A Multi-Domain Evaluation of Scaling in a General Episodic Memory
This paper reviews the implementation of episodic memory in Soar and presents an expansive evaluation of that system, demonstrating useful applications of episodi memory across a variety of domains, including games, mobile robotics, planning, and linguistics.
Efficiently Implementing Episodic Memory
Whether even with intractable asymptotic growth, it is possible to develop efficient algorithms and data structures for episodic memory systems that are practical for real-world tasks is explored.
An Improved Three-Weight Message-Passing Algorithm
We describe how the powerful "Divide and Concur" algorithm for constraint satisfaction can be derived as a special case of a message-passing version of the Alternating Direction Method of Multipliers
Towards efficiently supporting large symbolic declarative memories
This paper details data structures and algorithms for an efficient mechanism over a large set of retrievals, as well as for a class of activation bias, in the development of large-scale cognitive models.
Performance evaluation of declarative memory systems in Soar
This paper evaluates the declarative memories of Soar: working memory, semantic memory, and episodic memory, using a detailed simulation of a mobile robot running for one hour of real-time, indicating that the implementation is sufficient for tasks of this length.