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"A little knowledge is not so much dangerous as useless"
- Jim Harrison, in "The Beast That God Forgot to Invent"

|> Robotics
|> Connectionism
|> Cognitive Science
|> Neuroscience
|> Biology
|> Complexity
|> Misc - Programming + Design
|> Rejection List
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[ratings here are not guaranteed to be 100% impartial - most are given an A for outstanding, or left unrated]

<| ROBOTICS (17)

  • Understanding Intelligence, by Rolf Pfeifer + Christian Scheier (1999) - more or less the "bible" of embedded cognition and embodied robotics, stemming out of Rod Brooks' subsumption ideas from the mid 1980s. The biggest problem is, these devices tend to show complex agent-environment interactions, but not much in the way of general intelligence. Book is slightly wordy at 700-pages. (A)

  • How the Body Shapes the Way We Think, A New View of Intelligence, by Rolf Pfeifer + Josh Bongard (2007) - a much more terse update of the ideas in Understanding Intelligence. Big idea = how 'morphological computation' reduces and simplifies direct computing requirements. (A)

  • Vehicles, Experiments in Synthetic Psychology, by Valentino Braitenberg (1984) - a tiny book with some of the biggest ideas on robotics ever written. A true idea book. Braitenberg vehicles range from simplistic type 1 to complicated type 14, and with complexity of output behavior increasing almost exponentially. To comprehend this progression, think of the problem of the Sultan doubling the number of grains of rice on each successive square of a chessboard. Square 14 is beyond description. (A+)

  • Intelligent Systems: Architecture, Design, and Control, by Alex Meystel + James Albus (2002) - graduate-level textbook, regarding engineering of hierarchical-control systems for intelligent robotics. Core of the book is the multiresolutional, real-time Albus-node hierarchy that Albus has been working on for several decades. (A)

  • Mobile Robots, Inspiration to Implementation, by Joe Jones + Anita Flynn (1993) - the book that sparked the revolution in hobbyist robotics. Practical hardware design and practical subsumption-software examples. How is it possible for a 16 year-old book to still be so vital and useful? Think of this book as "square one". (A+)

  • Behavior Based Programming by Joe Jones (2003) - apt follow-on to the "Mobile Robots" book. Practical and highly useful programming techniques for small robots, but unfortunately which will never produce very much intelligence. Eg, "COG was an abject failure" (paraphrasing the king of symbolics, Marvin Minsky). (A)

  • Behavior-Based Robotics, by Ron Arkin (1998) - extensive academic-level discussion of subsumption and behavior-based robots, built in the decade following Rod Brooks' formulation of subsumption theory. (A)

  • Flesh and Machines, How Robots Will Change Us, by Rod Brooks (2002) - autobiographical discussion of Rod Brooks' life, as well as his formulation of robotic subsumption theory. Ultimately, Rod discusses why AI and robotics have "failed", thus far. Unfortunately, his final conclusion that "something is missing" (and which seems to amount to a rebirth of vitalism) leaves something to be desired. To wit, "... we may not be seeing some fundamental mathematical description of what is going on in living systems ... it might turn out that, for all the different aspects of biology that we model, there is a different juice that is missing". Missing juice, say what? In his own research, Rod subsequently initiated the 'living machines' project. Apparently, they got the juice.

  • Evolutionary Robotics, The Biology, Intelligence, and Technology of Self-Organizing Machines, by Stefano Nolfi + Dario Floreano (2000) - building real robots via application of the principles of evolution and neural systems. (A)

  • Inner Navigation, by Erik Jonsson (2002) - a brilliant little book on how humans navigate their worlds, directly applicable to robotics. Think rememberance of linked-lists of landmarks, rather than production of detailed internal 3-D map representations in memory. Eg, think of how you get from some common place to another. Then, ask how much detailed info you've committed to memory of places inbetween the obvious landmarks. (A)

  • Loving the Machine: The Art and Science of Japanese Robots, by T.N. Hornyak (2006) - discussion of Japanese robotic industry, history, and academics. The Japanese are heavy into building robot assistants for the elderly, largely as a result of the unique demographics of the country - rapidly aging population and few foreign workers. Large companies, such as Honda (cf, Asimo humanoid), have spend 100s of millions of dollars on research. Some Japanese researchers seem to think that construction of synthetic humans is the future (cf, the "Uncanny Valley"). (A)

  • Beyond AI: Creating the Conscience of the Machine, by J. Storrs Hall (2007) - obligatory overview of AI history, plus obligatory projections for AI in the future. Has some good ideas re 'cognitive servos' idea - another example of feedback in action.

  • Growing Up With Lucy, How to Build an Android in 20 Easy Steps, by Steve Grand (2003) - excellent first-person account of SG's attempt to build a hairy (and slightly bizarre) robotic orangutan using the general concept of neural maps governing brain operation (cf, Gerald Edelman & Sandra Blakeslee books). A lot of independent creative thought here. Ideas for the robot design are more interesting than the obligatory philosophizing in the last few chapters. (A)

  • Creation, Life and How to Make It, by Steve Grand (2000) - description of how mildly intelligent, synthetic/virtual creatures can be built from the bottom-up as networks of simple objects interacting in multi-layered feedback loops. Ie, the premise that "intelligence is a product of multiple layers of feedback". Instead of a top-down world of 'command-and-control', life is built as a bottom-up emergent world of 'nudge-and-cajole'. Ideas somewhat like an extension of Brooksian subsumptionism, and which might conceivably be used to design better robot brains. (A)

  • The Metaphorical Brain, An Introduction to Cybernetics as Artificial Intelligence and Brain Theory, by Michael Arbib (1971) - one of the last cybernetical holdouts. Advocates building robots following a brain metaphor, as "distributed action-oriented computation in layered somatotopically organized machines". Very much an engineering-oriented book. Topics include: visual preprocessing, system theory, AI+robotics, neural control of movement, memory+perception, resolving redundancy of command. Gives many examples of feedback at work in the nervous system, as well as engineering models of same. Much of the book is based upon prior work by Warren McCulloch, the great cybernetician.

  • Wired for War, The Robotics Revolution and Conflict in the 21st Century, by Peter Singer (2009) - sobering look at the future of mechanized battle. There are already many thousands of robots deployed in war zones.

  • Bio-Inspired Artificial Intelligence, by Dario Floreano & Claudio Mattiussi (2008) - includes chapters on: evolutionary, cellular, neural, developmental, immune, behavioral, and collective systems. Dust jacket: "each chapter presents computational approaches inspired by a different biological system". Last 200-pages include many examples of building robots using various of the principles described.


  • The Computational Brain, by Patricia S. Churchland + Terrence J. Sejnowski (1992) - nice overview of what was once called connectionism and is now called computational neuroscience. (A)

  • Self-Organization and Associative Memory, by T. Kohonen (1988) - possibly still the best book ever written on the topic area. Useful combination of mathematics, ideas, and techniques that actually work. (A+)

  • Perceptrons, by M. Minsky + S. Papert (1969, 1987) - brilliant mathematical analysis of "single-layer" perceptrons, but wasted effort at quenching the cresting wave of connectionism. Considered to be "the" classic mathematical analysis on neural-nets. The appendix of the 2nd edition brilliantly lays out the limitations of connectionism in general, but without seeming to understand the generalities and extensions inherent with use of multi-layer perceptrons. (A)

  • Parallel Distributed Processing, Explorations in the Microstructure of Cognition, 2 volumes + handbook, by D.E. Rumelhart + J.L. McClelland (1986) - the hands-down grand manifesto, signalling the rebirth of modern connectionism, after premature death at the hands of Perceptrons (above). The real key to getting past the limitations discussed in Perceptrons is the use of multi-layered networks with nonlinear activation functions, plus use of recurrent feedback in certain cases. Dozens of creative connectionist architectures, that all solve unique problems, plus free (DOS) software in the related handbook. (A+)

  • The Engine of Reason, The Seat of the Soul, a Philosophical Journey into the Brain, by Paul Churchland (1999) - provides introductory material on many areas of brain science, with emphasis on perception, language, social interactions, the usual obligatory [and inconclusive] discussion of consciousness, and with discussion of how many such tasks might be implemented using connectionist networks. Contains good information on sensory coding and especially stereo-vision. Stresses how recurrent neural networks can solve complex problems far better than feedforward nets. Comes with a collapsible stereoscope to illustrate examples. The last half of the book is mainly philosophical-conjecture, for those so inclined [oof!].


  • Thinking in Pictures, and Other Reports From My Life With Autism, by Temple Grandin (1995) - how the other half thinks, not with symbols, but with pictures. TG is an absolutely brilliant resource, namely an autistic who can express how her inner world operates, and to the great benefit of those of us less gifted. (A+). See also, Animals in Translation by TG (2005).

  • Being There, Putting Brain, Body, and World Together Again, by Andy Clark (1999) - Andy's most "brilliant" book about embedded cognition - "understanding brains as controllers for embodied activity". Action loops, scaffolded minds, emergence and evolution, action-oriented representation, and lots of robotics. (A). See also secondary list.

  • The Society of Mind, by Marvin Minsky (1985) - still brilliant after all these years, except that the brain really "is" as much hierarchy as heterarchy. Also, it's not clear to what extent it ever uses recursive subroutines (patterned after computer science). (A)

  • Action in Perception, by Alva Noe (2001) - illustrates what happens when someone approaches a problem in science from a pre-ordained philosophical stance (such as behaviorism). Chapter 1, line 1: "The main idea of this book is that perceiving is a way of acting". Right, and mental imagery and dreaming are just internal ways of acting. Included because of the selection and coverage of scientific material, not for the conclusions drawn. (A, with qualifications)

  • The Muse in the Machine, by David Gelernter (2002) - DG's theory of high-focus [rational] and low-focus [emotional] thought processes, as a cognitive spectrum extending from narrowly-focused symbolic processing on one end, down to manipulation, comparison, and filtering across a wide range of episodic memories on the other end. (A)

  • On Intelligence, by Jeff Hawkins (2004) - a computer scientist poaches on brain theory. Think HTM = hierarchical temporal memory. More background neuroscience would be nice, but H. nicely captures the significance of sensory- and motor-side brain hierarchies. (Koestler did it a little better, re 'Ghost ...').

  • A Mind So Rare, the Evolution of Human Consciousness, by Merlin Donald (2001) - just about the only discussion of consciousness encountered so far that puts it into the serious context of bottom-up biological evolution, rather than ordained and prescribed top-down philosophy. Evolved hierarchy is king. One could design a robot mind with the ideas given in this book. (A+)

  • Mind Over Machine, the Power of Human Intuition and Expertise in the Era of the Computer, by Hubert + Stuart Dreyfus (1986) - the Dreyfuses were "present at the creation" of AI, so to speak; namely, working with Rand Corp in the late 1950s when Simon+Newell started writing so-called intelligent programs on the incipient computers of the era. Think Johnniac. And they've been harse critics of the over-hyping of symbolic approaches, including expert systems, ever since. Book has good accounts on the 5-steps from novice-to-expert [so-called 'expert systems' are actually novice level], limits of logic machines, and sober realities of AI. Interestingly, all their criticisms are still relevant and unsatisfied today, 25-years later. As Rod Brooks would say, "something is missing". Hint - best section in the book is 'AI Without Information Processing' in chapter 3. (A)

  • The Scientist in the Crib, Minds, Brains, and How Children Learn, by Alison Gopnik et al (1999) - an extremely easy intro to child development, obviously geared towards the wider parenting audience rather than the technical / scientific. From a cognitive perspective, a baby has to learn to solve 3 major problems: that of beings with 'Other Minds', that of a persistent 'External World', and that of 'Language'. The authors' premise is that humans are born with simple 'pre-formed' (innate) cognitive solutions for these problems, which are 're-formed' several times over in early life due to gaining specific information from the real-world; this idea is somewhere inbetween genetically-determined stages and pure-association paradigms. The basic premise for topics such as "why it is difficult for adults to learn a second language?" is, not because of any so-called biological critical periods, but rather that once a paradigm has been established, it interferes with establishment of competing paradigms (that use the same facilities). One of many highly-debated hypotheses; eg, feral children never learn even one language properly (the book authors dismiss this uncritically).

    See also secondary list.

    <| NEUROSCIENCE (14)

  • The Remembered Present, A Biological Theory of Consciousness, by Gerald Edelman (1987) - (also author of 5 or 6 similar and more recent pop-sci books) - 20-years later, and G.E. is still vastly underrated by most mainstream cognitive scientists. When you're a Nobel Prize winner, you get to have your own research institute. And his team builds nice robots too. (A+)

  • The Body Has a Mind of Its Own, How Body Maps in Your Brain Help You Do (Almost) Anything Better, by Sandra and Matthew Blakeslee (2007) - discusses what are possibly the most important new discoveries of how malleability in the brain controls the body to produce behavior. Body maps, body maps, and more body maps. The inner homunculus [Penfield's original one, not the philosophical strawman] run amuck. (A+) (cf, Dawkins The Ancestor's Tale below).

  • The Visual Brain in Action, by A.D. Milner + M.A. Goodale (1995) - in essence, Noe's book without the lapse into one-sided philosophy. Just the science, mister. Book is notable for distinquishing specific processing areas related to different forms of visual activity, eg, pattern recognition vs sensory-motor coordination, etc. Bottom line, there are several different types of visual mechanisms running in parallel, as opposed to one single overriding scheme of operation. (A)

  • Journey to the Centers of the Mind, Toward a Science of Consciousness, by Susan Greenfield (1995) - Susan's idea of neuronal gestalts. (cf, Edelman above).

  • The Ghost in the Machine, by Arthur Koestler (1968) - early and utterly brilliant discussion of hierarchical brain theory. (A+) (note - book is extremely expensive today, but the same theory is also described in Koestler's book Janus: a Summing Up, typically available for about $1 on Amazon).

  • The Biology and Evolution of Language, by Phil Lieberman (1984) - scientific treatise on how language may have evolved out of neural circuitry previously evolved for other purposes, such as breathing and eating and grunting. Funny how evolution works that way, to modify and utilize what's already available (ie, evolved earlier). (A)

  • Cortex and Mind, Unifying Cognition, by Joaquin Fuster (2003) - indepth coverage of brain architecture, especially related to perception, memory, and action. Concentration on hierarchical organization, and interactions between frontal (executive) and posterior (sensory) cortical regions. In our opinion, one of the best single accounts of the neuroscience of cognition. (A+)

  • Reading in the Brain, The Science and Evolution of a Human Invention, by Stanislas Dehaene (2009) - a truly excellent account of brain mechanisms involved in reading, and how they might have evolved; a scheme involving a multi-level hierarchical arrangement of parallel visual and auditory mechanisms. Also notable for presenting a good overview of recent research on cortical visual neurophysiology. Possibly the best single book on neuroscience that we've read recently. (A+)

  • Going Inside, A Tour Round a Single Instant of Consciousness, by John McCrone (1999) - a nice exposition of brain operation from a (dynamical) systems perspective, of interconnected parts. Consciousness and all other behavioral activities involve continuous, on-going activity in highly-interconnected brain regions, much of it below the level of awareness. The computer and linear information-processing models of brain processing are deadends. For a good introductory overview of brain science, start here. (A)

  • My Stroke of Insight, a Brain Scientist's Personal Journey, by Jill Bolte Taylor (2006) - like Temple Grandin, JBT is another invaluable resource where a scientist is able to observe and analyze their own mental irregularities ... from the inside. In this case, it was a massive hemorraghic stroke that incapacitated much of the left-hemisphere of the brain, severely affecting language, planning, sequential behavior. Most profound was loss of "brain chatter", the background mental dialogue used for linearly organizing one's behavior, and perpetuating the feeling of a coherent historical self. The result was ascendency of right-hemisphere holistic (essentially Buddhistic) consciousness. Supports the notion that left-brain = thinking-in-symbols, right-brain = thinking-in-pictures. Practically speaking, a manual for survival. (A, for incredible)

  • Images of Mind, by Michael Posner & Marcus Raichle (1994) - in-depth description of early brain imaging research pertaining to many varieties of cognitive activity. A really fine overview, looking at wide systems-level activity. (A)

  • Complex Worlds from Simpler Nervous Systems, by Frederick R. Prete (2004) - 11 chapters by different authors on the nervous and behavioral systems of different species, including amphibians, spiders, bees, mantis, butterfly, crayfish, octopus, and grasshopper. Even a relatively primitive creature, like a toad, has over 30 different brain areas allocated to visual-olfactory sensory-motor behavior. Excellent all-around. (A)

  • Sight Unseen, An Exploration of Conscious and Unconscious Vision, by M.A. Goodale + A.D. Milner (2004) - a shorter and updated version of The Visual Brain in Action. Summary of recent research on the 2 visual systems in mammalian brain, the "what" system in ventral cortex vs the "where" system in dorsal cortex. The prior has a scene-based frame of reference and deals with perception and recognition, while the latter is body-egocentric and deals with local just-in-time visuomotor behavior. Brilliant explanation of how operation of parallel brain systems can fool the naive philosopher of mind. (A)

    See also secondary list.

    <| BIOLOGY (10)

  • Endless Forms Most Beautiful, the New Science of Evo-Devo and the Making of the Animal Kingdom, by Sean Caroll (2005) - hard science is finally getting a handle on developmental biology. The big idea = Homeobox conservation - we're all really just modified worms, with bilateral symmetry, and head on one end and anus on the other. (A+)

  • The Birth of the Mind, How a Tiny Number of Genes Creates the Complexities of Human Thought, by Gary Marcus (2004) - discussion of why the limited amount of information encoded in DNA really 'can' produce seemingly endless varieties of lifeforms most beautiful. Think DNA and protein networks, multiple feedback interaction pathways, time-dependent DNA/protein interactions, and combinatorics in gene expression (ie, vectors with 12,000 dimensions). (A)

  • Big Brain, The Origins and Future of Human Intelligence, by Gary Lynch + Richard Granger (2007) - nice overview of brain evolution and organization, albeit including a highly controversial (and largely rejected) idea about an unknown species of big-brained individuals (ie, Boskops, meaning 'almost gods'). Granger's neural models alone are worth much more than the price of admisssion. (A)

  • In the Blink of An Eye, How Vision Sparked the Big-Bang of Evolution, by Andrew Parker (2003) - title speaks for itself; putative hypothesis that evolution of vision was largely responsible for the Cambrian explosion of animal species 500MY ago. Think trilobites as the original visual predators.

  • Climbing Mount Improbable, by Richard Dawkins (1996) - popular discussion of how evolution works, not by taking one gigantic leap up the sheer front face of Mount Improbable, but by taking countless micro-steps up the gentle slopes of its backside. Notable for its chapter on how the eye evolved separately 40 different times.

  • The Ancestor's Tale, A Pilgrimage to the Dawn of Evolution, by Richard Dawkins (2005) - many examples of interesting evolved species types, down through the various Phyla. Due to the more serious emphasis on scientific content over branded opinion than in most of his usual books, this one rates an (A). The section on multiple internal sensory-motor maps in platypus (Platypunculus!) and blind star-nosed moles is excellent (cf, Blakeslee The Body Has a Mind of Its Own above).

  • What Evolution Is, by Ernst Mayr (2001) - (along with many other books) - neo-Darwinism, completing the theory. What Darwin didn't know. Any book by Ernst Mayr rates an (A).

  • The Plausibility of Life, Resolving Darwin's Dilemma, by Marc Kirschner + John Gerhart (2005) - how the new science of 'Systems Biology' approaches the problem of evolution and development of living matter. Sections on: conserved core processes (cf, Sean Carroll), modularity+compartmentation, weak regulatory links, facilitated variation, irreducible complexity, cell signalling - sounds a lot like engineering. (A)

  • General Systems Theory, by Ludwig von Bertalanfy (1968) - material dating to pre-Cybernetics, early attempt at formulating mathematical techniques for the rigorous study of biology. Probably helped launch the profession of modern systems engineering. (A+). (see also, Robots, Men, and Minds; Psychology in the Modern World by the same author, 1966).

  • Wetware, A Computer in Every Living Cell, by Dennis Bray (2009) - mostly about molecular biology; interesting book on how cells work, with special emphasis on protein mechanisms, and with loose analogies to [extremely more simplistic] simulated systems. Confuses computation with process; better than "computer" would have been "every cell is an extremely complex, massively parallel system involving billions of nonlinear, interacting chemical and mechanical feedback processes; where all processes are analog, but some appear to be digital (on/off) in nature". But how tonque-twisted is that? Much easier to say "computer"; what used to be chemical reaction kinetics in olden days is now elevated to the top-rung of metaphorical 'computation' in the age of computers. From an EE perspective, a cell is much more like a massive circuit or heterogeneous network than a computer.


  • The Web of Life, A New Scientific Understanding of Living Systems, by Fritjof Capra (1996) - a brilliant non-theoretical overview of how complexity theory and emergence pertain to biology. Shows how chaotic unpredictability can result from an equation as trivially simple as: x' = k * x * (1 - x), an equation which, in fact, contains all the attributes of a complex emergent system: gain, nonlinearities, plus positive and negative feedback terms. (A)

  • Exploring Complexity, An Introduction, by Gregoire Nicolis + Ilya Prigogine (1989) - theoretical (academic-level) coverage of complexity theory, bifurcations galore, all the equations of attractor space, and more. (A)

  • Hidden Order, How Adaptation Builds Complexity, by John Holland (1995) - you could build a working robotic system out of these theoretical ideas. (A)

  • Self-Organization in Biological Systems, by Scott Camazine and 5 others (2003) - semi-theoretical coverage of self-organizing systems in biology. Includes multiple chapters with extensive descriptions of computer simulations, eg, pattern formation in bacteria, fish schooling, termite mound building, trail formations in ants. (A+)

  • Turbulent Mirror, An Illustrated Guide to Chaos Theory and the Science of Wholeness, by John Briggs + F. David Peat (1989) - nice popular introduction to chaos theory, emphasizing the important role of nonlinear feedback to self-organization.

  • Signs of Life, How Complexity Pervades Biology, by Ricard Sole + Brian Goodwin (2000) - popular introduction to complexity theory. Includes a few algorithms, useful for initial attempts at simulating systems with emergent (unexpected) characteristics. Eg, genetic networks, Kauffman NK model, edge of chaos, fractal cities, market crashes, neural chaos.


  • Dreaming in Code, by Scott Rosenberg (2007) - a really great book discussing both the history and foibles of software programming in general, and concentrating specifically on an attempt to build an open-source PIM using a similar philosophy to how Linux got built. Unfortunately, also ... (a) how to spend between 50 & 100 man-years to produce an open-source feature-riven calender program, (b) all the ways to bog down a large software effort, (c) how a team of the best and the brightest programmers can get killed by recursive featuritis (cf, "running in circles"), (d) what happens when your primary goal is to be all things to all people, (e) "how friggin come it worked for Linus?", and (f) [obligatory to include the age-old nugget] on why the best is enemy to the good. Highly recommended to anyone who codes, and does more than just take orders and cash the checks. (A+)

  • misc programming books

  • Fab: the Coming Revolution on Your Desktop - From Personal Computers to Personal Fabrication, by Neil Gershenfeld - about the future use of small-scale fabrication machines to provide utilitarian technology for individuals and populations in low-tech areas of the world. N.G. is member of the MIT Media Lab. (A)

  • The Design of Future Things, by Donald Norman (2007) - similar to DN's other design-of books, with emphasis on human-technology interactions, and attempts to make technology more intelligent. The biggest problem with [attempting to build] intelligent machines is in their inability to understand the context of situations. Good metaphor in human-horse interaction: "loose reins" = horse in control, "tight reins" = human in control. (A)

    <| PHILOSOPHY (2) [difficult to find something here of real use to robotics] - also

  • Darwin's Dangerous Idea, by Dan Dennett (1995) - trying to find an area of overlap between philosophy and reality, ie evolved organics. A useful contribution here, vis-aviz robotics, is the idea of Darwinian, Skinnerian, Popperian, and Gregorian creatures. (A)

  • Freedom Evolves, by Dan Dennett (2003) - from a noted philosopher, a book about how 'degrees of freedom', or the ability to act in more complex, intelligent, and rich ways, evolved in orga. Holding the line against 'creeping exculpation' - the sort of modern .. "I'm not responsible for anything, cause I don't have free will, and the behaviorists and philosophers tell me so" .. copout. DOH. Not just another circular argument about 'free will'. (A)

    See also secondary list.


    See secondary list.

    [see: Carroll, Endless Forms Most Beautiful]

    <| Small list of people with really good stuff to say

  • Gerald Edelman
  • Richard Granger
  • Rick Grush
  • Valentine Braitenberg
  • Temple Grandin
  • Rolf Pfeifer
  • Sean Carroll
  • the early (grounded) Andy Clark

    Final list of choice books for roboticists

  • Understanding Intelligence, plus How the Body Shapes the Way We Think
  • Vehicles, Experiments in Synthetic Psychology
  • Mobile Robots, Inspiration to Implementation
  • Inner Navigation
  • Growing Up With Lucy
  • The Remembered Present
  • Being There, Putting Brain, Body, and World Together Again
  • Endless Forms Most Beautiful
  • Dreaming in Code

    Books good for inspiring deep scientific conjecture

  • The Plausibility of Life
  • The Web of Life
  • The Birth of the Mind
  • The Ghost in the Machine
  • A Mind So Rare


    <| TOP

    © www.robotrambler.com, orig June 2009, updated July 2010