Real-Time Moving Target Evaluation Search

Undeger, Cagatay
Polat, Faruk
In this correspondence, we address the problem of real-time moving target search in dynamic and partially observable environments, and propose an algorithm called real-time moving target evaluation search (MTES). MTES is able to detect the closed directions around the agent and determines the estimated best direction to capture a moving target avoiding the obstacles nearby. We have also developed a new prey algorithm (Prey-A*) to test the existing and our predator algorithms in our experiments. We have obtained an impressive improvement over moving target search, real-time target evaluation search, and real-time edge follow with respect to path length. Furthermore, we have also tested our algorithm against A*.


Real-Time Moving Target Search
Undeger, Cagatay; Polat, Faruk (2007-11-23)
In this paper, we propose a real-time moving target search algorithm for dynamic and partially observable environments, modeled as grid world. The proposed algorithm, Real-time Moving Target Evaluation Search (MTES), is able to detect the closed directions around the agent, and determine the best direction that avoids the nearby obstacles, leading to a moving target which is assumed to be escaping almost optimally. We compared our proposal with Moving Target Search (NITS) and observed a significant improvem...
Random Set Methods Estimation of Multiple Extended Objects
Granstrom, Karl; Lundquist, Christian; Gustafsson, Fredrik; Orguner, Umut (Institute of Electrical and Electronics Engineers (IEEE), 2014-06-01)
Random set-based methods have provided a rigorous Bayesian framework and have been used extensively in the last decade for point object estimation. In this article, we emphasize that the same methodology offers an equally powerful approach to estimation of so-called extended objects, i.e., objects that result in multiple detections on the sensor side. Building upon the analogy between Bayesian state estimation of a single object and random finite set (RFS) estimation for multiple objects, we give a tutorial...
Observability Through a Matrix-Weighted Graph
Tuna, Sezai Emre (Institute of Electrical and Electronics Engineers (IEEE), 2018-07-01)
Observability of an array of identical linear time-invariant systems with incommensurable output matrices is studied, where an array is called observable when identically zero relative outputs imply synchronized solutions for the individual systems. It is shown that the observability of an array is equivalent to the connectivity of its interconnection graph, whose edges are assigned matrix weights. Moreover, to better understand the relative behavior of distant units, pairwise observability that concerns wi...
Positive impact of state similarity on reinforcement learning performance
Girgin, Sertan; Polat, Faruk; Alhaj, Reda (Institute of Electrical and Electronics Engineers (IEEE), 2007-10-01)
In this paper, we propose a novel approach to identify states with similar subpolicies and show how they can be integrated into the reinforcement learning framework to improve learning performance. The method utilizes a specialized tree structure to identify common action sequences of states, which are derived from possible optimal policies, and defines a similarity function between two states based on the number of such sequences. Using this similarity function, updates on the action-value function of a st...
A state prediction scheme for discrete time nonlinear dynamic systems
Demirbaş, Kerim (Informa UK Limited, 2007-01-01)
A state prediction scheme is proposed for discrete time nonlinear dynamic systems with non-Gaussian disturbance and observation noises. This scheme is based upon quantization, multiple hypothesis testing, and dynamic programming. Dynamic models of the proposed scheme are as general as dynamic models of particle predictors, whereas the nonlinear models of the extended Kalman (EK) predictor are linear with respect to the disturbance and observation noises. The performance of the proposed scheme is compared wi...
Citation Formats
C. Undeger and F. Polat, “Real-Time Moving Target Evaluation Search,” IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, pp. 366–372, 2009, Accessed: 00, 2020. [Online]. Available: