Publications

Cognitive Science Research Papers (CSRP)

Here is a list of some Cognitive Science Research Paper (CSRP) technical reports relevant to evolutionary and adaptive systems research. CSRPs are produced within the Department of Informatics. Click on the report number to see the abstract, and links to the ftp'able version. There is a full listing of the reports available from Informatics here.

• (584) Marieke Rohde, Ezequiel Di Paolo: 'Value signals' and adaptation: an exploration in evolutionary robotics
• (583) Manuela Jungmann, Nicolas Villar: BodyPresent: social coordination of embodied stillness
• (577) Thorsten Prante, Brian Meyers, Geraldine Fitzpatrick, Lonnie Harvel (eds): ECHISE 2005. Proceedings of 1st international workshop on exploiting context histories in smart environments
• (575) Steve Torrance: Thin phenomenality and machine consciousness
• (574) Ron Chrisley, Rob Clowes, Steve Torrance: Next-generation approaches to machine consciousness
• (572) Miguel Garvie, Adrian Thompson: Low overhead self-checking combinatorial and sequential circuits designed by evolution
• (568) Blay Whitby:The myth of AI failure
• (563) Kingsley Sage, A. Jonathan Howell, Hilary Buxton: Developing context sensitive HMM gesture recognition
• (562) A. Jonathan Howell, Kingsley Sage, Hilary Buxton: Developing task-specific RBF hand gesture recognition
• (560) Stephen Drake: C(N,K) landscapes: an investigation of epistasis and crossover in real-valued GAs
• (551) Terry Stewart: Learning in artificial life: conditioning, concept formation and sensorimotor loops
• (549) Tom Smith, Phil Husbands, Michael O'Shea: Temporally adaptive networks: analysis of GasNet robot controllers
• (548) Ezequiel Di Paolo: Evolving robust robots using homeostatic oscillators
• (536) Ezequiel A. Di Paolo: Artificial life and historical processes
• (535) Tom Smith, Phil Husbands, Michael O'Shea: Evolvability, neutrality and search difficulty
• (534) Tom Smith, Phil Husbands, Michael O'Shea: Characterising fitness landscapes through evolvability
• (533) Blay Whitby: Flying lessons: what can aviation investigations tell other disciplines about the human-computer interface?
• (530) Stephen Drake, Phil Husbands: Survival of the sickest: a site-specific recombination operator for accelerated function optimization
• (529) Ezequiel Di Paolo: Rhythmic and non-rhythmic attractors in asynchronous random Boolean networks
• (524) Terry Stewart: Neural models of concept formation and conditioning: a literature review
• (519) Rudi Lutz: Evolving good hierarchical decompositions of complex systems
• (515) Matt Quinn, Lincoln Smith, Giles Mayley, Phil Husbands: Evolving formation movement for a homogeneous multi-robot system: teamwork and role-allocation with real robots
• (510) Shimon Edelman, Nathan Intrator: Computational models of perceptual learning
• (506) Anil Seth: A cybernetic perspective on the role of noise in the iterated prisoner's dilemma
• (504) Chris Thornton: Truth-from-trash learning and the mobot footballer
• (498) Phil Husbands, Tom Smith, Nick Jakobi and Michael O'Shea: Better living through chemistry: evolving gasnets for robot control
• (497) Nick Jakobi: Running across the reality gap: octopod locomotion evolved in a minimal simulation
• (482) Margaret A. Boden: Is metabolism necessary?
• (479) Paul Layzell: The 'evolvable motherboard'. A test platform for the research of intrinsic hardware evolution
• (462) Joe Faith: In defence of functional analysis
• (461) Andrew Wuensche: Attractor basins of discrete networks. Implications on self-organisation and memory
• (460) Julie Rutkowska: Computation, dynamics and sensory-motor development
• (459) Dave Cliff and Jason Noble: Knowledge-based vision and simple visual machines
• (457) Nick Jakobi: Evolutionary robotics and the radical envelope of noise hypothesis
• (455) Malcolm McIlhagga and Phil Husbands: The application of a distributed genetic algorithm to a generic scheduling system
• (451) Chris Thornton: A no-strings representation theory for adaptive researchers
• (450) Chris Thornton: Backpropagation can't do parity generalisation
• (449) Chris Thornton: Unsupervised constructive learning
• (448) Chris Thornton: The inductive roots of abduction: a task analysis
• (447) Chris Thornton: Is transfer inductive?
• (446) Bill Keller and Rudi Lutz: A new crossover operator for rapid function optimisation using a genetic algorithm
• (445) Ezequiel A. Di Paolo: An investigation into the evolution of communicative behaviours
• (441) Ronald Lemmen: Embodiment for non-Cartesians
• (434) Stephen Grand, Dave Cliff and Anil Malhotra: Creatures: artificial life autonomous software agents for home entertainment
• (425) Frederic Gruau and Kameel Quatramaran: Cellular encoding for interactive evolutionary robotics
• (423) Nick Jakobi: Harnessing morphogenesis
• (422) Nick Jakobi: Facing the facts: necessary requirements for the artificial evolution of complex behaviour
• (408) M. McIlhagga, P. Husbands and R. Ives: A comparison of optimization techniques for integrated manufacturing planning and scheduling
• (420) Jason Noble and Dave Cliff: On simulating the evolution of communication
• (414) Seth Bullock and Dave Cliff: Modelling biases and biasing models: the role of 'hidden preferences' in the artificial co-evolution of symmetrical signals
• (412) Ezequiel A. Di Paolo: A computational model of speciation in non-uniform environments without physical barriers
• (409) Giles Mayley: No pain, no gain: landscapes, learning costs and genetic assimilation
• (401) Chris Thornton: Brave mobots use representation
• (400) Chris Thornton: Parity: the problem that won't go away
• (399) Chris Thornton: Why GAs are hard to use
• (397) Adrian Thompson, Inman Harvey and Philip Husbands: Unconstrained evolution and hard consequences
• (396) Ibrahim Kuscu: Incrementally learning the rules for supervised tasks: the Monk's problems
• (395) Ibrahim Kuscu: Evolution of learning rules for supervised tasks II: hard learning problems
• (394) Ibrahim Kuscu: Evolution of learning rules for supervised tasks I: simple learning problems
• (385) Adrian Thompson: Evolving fault-tolerant systems
• (384) Seth G. Bullock: Co-evolutionary design: implications for evolutionary robotics
• (379) Inman Harvey and James V. Stone: Unicycling helps your French: spontaneous recovery of associations by learning unrelated tasks
• (378) Geoffrey F. Miller: Artificial life as theoretical biology: how to do real science with computer simulation
• (373) Pedro Paulo Balbi de Oliveira: An empirical exploration of computations with a cellular-automata-based artificial life world
• (370) Julie C. Rutkowska: Can development be designed? What we may learn from the Cog Project
• (369) Julie C. Rutkowska: Reassessing Piaget's theory of sensorimotor intelligence: a view from cognitive science
• (368) Adrian Thompson: Evolving electronic robot controllers that exploit hardware resources
• (364) Peter de Bourcier and Michael Wheeler: Aggressive signaling meets adaptive receiving: further experiments in synthetic behavioural ecology
• (361) Chris Thornton: Learning where to go without knowing where that is: the acquisition of a non-reactive mobot behaviour by explicitation
• (359) Chris Thornton: Why conditional approach is hard to learn
• (357) Michael Wheeler and Peter de Bourcier: How not to murder your neighbor: using synthetic behavioural ecology to study aggressive signaling
• (355) Kyran Dale: Evolving neural network controllers for task defined robots
• (354) Chris Thornton: The 1994 COGS Robotics Challenge
• (351) James V Stone: Computer Vision: What is the object?
• (347) Dave Cliff and Susi Ross: Adding Temporary Memory to ZCS
• (346) Andrew Wuensche: The emergence of memory: categorisation far from equilibrium
• (338) Dave Cliff: Neuroethology, Computational
• (329) James V. Stone: Evolutionary robots: our hands in their brains?
• (327) Michael Wheeler: Active perception in meaningful worlds
• (323) Dave Cliff: AI and A-Life: Never mind the blocksworld
• (321) Andrew Wuensche: Complexity in One-D Cellular Automata: gliders, basins of attraction and the Z parameter
• (320) Michael Wheeler: For Whom The Bell Tolls? The Roles of Representation and Computation in the Study of Situated Agents
• (319) Ibrahim Kuscu and Chris Thornton: Design of artificial neural networks using genetic algorithms: review and prospect
• (318) Dave Cliff, Inman Harvey and Phil Husbands: General visual robot controller networks via artificial evolution
• (317) Inman Harvey, Phil Husbands and Dave Cliff: Seeing the light: artificial evolution, real vision
• (311) Geoffrey F. Miller and Dave Cliff: Co-Evolution of Pursuit and Evasion I: Biological and Game-Theoretic Foundations
• (310) Andy Clark and Pepa Toribio: Doing without representing?
• (308) Chris Thornton: Supervised learning of conditional approach: a case study
• (307) Margaret A. Boden: Autonomy and Artificiality
• (305) D. Cliff: Artificial Intelligence or Artificial Insects?
• (304) Peter de Bourcier and Michael Wheeler: Signalling and territorial aggression: an investigatioin by means of synthetic behavioural ecology
• (298) Horst Hendriks-Jansen: Scientific explanations of behaviour: the approach through evolution and learning
• (297) Horst Hendriks-Jansen: Scientific explanations of behaviour: the approach through formal task-description
• (291) Andy Clark and Chris Thornton: Trading Spaces: computation, representation and the limits of learning
• (290) Geoffrey F. Miller and Jennifer J. Freyd: Dynamic mental representations of animate motion: The interplay among evolutionary, cognitive, and behavioural dynamics
• (287) Matthew Elton: Human and animal consciousness
• (284) Michael Wheeler: Explaining the behaviour of springs, pendulums, and cognizers
• (282) Chris Thornton: Representation as function-hiding
• (281) Andrew Wuensche: The Ghost in the Machine: Basins of attraction of random Boolean Networks
• (279) Julie C. Rutkowska: An Infant's-eye view of adaptive behaviour and change in situated systems
• (278) Inman Harvey: The puzzle of the persistent question marks: a case study of genetic drift
• (277) Peter G.R. de Bourcier: Animat navigation using visual landmarks
• (267) I. Harvey, P. Husbands and D. Cliff: Genetic convergence in a species of evolved robot control architectures
• (265) P. Husbands, I. Harvey and D. Cliff: Analysing recurrent dynamical networks evolved for robot control
• (264) D. Cliff, P. Husbands and I. Harvey: Analysis of evolved sensory-motor controllers
• (263) D. Cliff and S.G. Bullock: Adding 'Foveal Vision' to Wilson's Animat
• (259) Ronald L. Chrisley: Connectionism, cognitive maps and the development of objectivity
• (256) D. Cliff, I. Harvey and P. Husbands: Incremental evolution of neural network architectures for adaptive behaviour
• (250) Robert Davidge: Processors as organisms
• (248) Pedro Paulo Balbi de Oliveira: Enact: an artificial-life world in a family of cellular automata
• (246) Ronald L. Chrisley: Taking embodiment seriously: non-conceptual content and computation
• (245) Inman Harvey: Untimed and misrepresented: connectionism and the computer metaphor
• (237) Pedro Paulo Balbi de Oliveira: Methodological issues within a framework to support a class of artificial life worlds in cellular automata
• (231) Philip Husbands: An ecosystems model for integrated production planning
• (223) Inman Harvey: The SAGA cross: the mechanics of recombination for species with variable length genotypes
• (222) Inman Harvey: Evolutionary robotics and SAGA: the case for hill crawling and tournament selection
• (221) Inman Harvey: Species Adaptation Genetic Algorithms: a basis for a continuing SAGA
• (220) D. Cliff, P. Husbands and I. Harvey: Evolving visually guided robots
• (219) I. Harvey, P. Husbands and D. Cliff: Issues in evolutionary robotics
• (210) Pedro Paulo Balbi de Oliveira: A cellular automaton to embed genetic search
• (206) D. Cliff: Neural networks for visual tracking in an artificial fly
• (163) D. Cliff: Network control for animate vision with nonuniform sampling
• (162) D. Cliff: Computational Neuroethology: a provisional manifesto