Search Results for author:
Found 7 papers, 1 papers with code
Potential Field Guided Actor-Critic Reinforcement Learning
Secondly, we combine the reward-based critic with a potential-field-based critic to formulate the proposed potential field guided actor-critic reinforcement learning approach (actor-critic-2).
Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning
In this paper, we consider the problem of large scale multi agent reinforcement learning.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Study of dynamical system based obstacle avoidance via manipulating orthogonal coordinates
A orthogonal coordinates manipulating approach is proposed by introducing rotating matrix to solve the local minimal problem and provide more reasonable motions in 3-D or higher dimension space.
Crowd collectiveness measure via graph-based node clique learning
In this paper, we try to measure the collectiveness of a crowd system by the proposed node clique learning method.
Robust Dictionary based Data Representation
This assumption is enforced in this paper by investigating the coefficients of corrupted samples.
Agglomerative clustering and collectiveness measure via exponent generating function
A novel agglomerative clustering method is proposed by utilizing the path integral to define the affinity measure.
Semi-supervised Data Representation via Affinity Graph Learning
We incorporate the new Laplacian regularizer into the unsupervised data representation to smooth the low dimensional representation of data and make use of label information.
