By Howard Bowman, Christophe Labiouse
This ebook collects jointly refereed types of papers awarded on the 8th Neural Computation and Psychology Workshop (NCPW 8). NCPW is a well-established workshop sequence that brings jointly researchers from various disciplines, similar to man made intelligence, cognitive technological know-how, laptop technological know-how, neurobiology, philosophy and psychology. The articles are concentrated at the topic of connectionist modelling of cognition and perceptionn.
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This publication collects jointly refereed types of papers offered on the 8th Neural Computation and Psychology Workshop (NCPW 8). NCPW is a well-established workshop sequence that brings jointly researchers from diverse disciplines, resembling synthetic intelligence, cognitive technology, laptop technology, neurobiology, philosophy and psychology.
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Extra info for Connectionist Models of Cognition, Perception II (Progress in Neural Processing)
Lbpez-Moliner and P. L. Cobos for their useful comments. We thank specially two anonymous reviewers and their very meticulous work. 48 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. H. Sun and B. J. Frost. Computation of different optical variables of looming objects in pigeon nucleus rotundus neurons. Nature Neurosci. 1, 296 (1998). J. L. Elman. Finding structure in time. Cognitive Science. 14, 179 (1993). J. R. Tresilian. The revised Tau hypothesis: A consideration of Wann’s analysis.
Detwiler. Information used in judging impending collision. Perception. 8,647 (1979). F. X. Li and M. Laurent. Occlusion rate of ball texture as a source of velocity information. Percept. Motor Skills. 81, 871 (1995). P. R. DeLucia. Pictorial and motion-based information for depth perception. J. Exp. Psychol. Hum. Percept. Perform. 17,738 (1991). P. R. DeLucia and R. Warren. Pictorial and motion-based depth information during active control of self-motion: Size-arrival effects on collision avoidance.
001), so the slowest of the overlapping speeds were responded to earlier than the fastest. In the optical state space, the axes are visual angle and rate of expansion. So, different response strategies can be drawn as linear combinations of both primitives. 46 Fast-Range Group Slow-Range Group 2 a ...... 4,5 W L S e s d o n1 Sesdon5 ....... J -1 -1,5 wlapplw Speedr OverlapphgSpeeds Figure 3. Results of simulation 2. The X-axis represents the three overlapping speeds and the Y-axis represents the performance of the SRNN: the correct responses were coded as 0, anticipate responses were coded as 1 for each step of anticipation and late response were coded as -1 for each step of delay.
Connectionist Models of Cognition, Perception II (Progress in Neural Processing) by Howard Bowman, Christophe Labiouse