As I develop outlines, roughs and such, I will add links. If any of this interests you let me know (NOTE: remove 'NOISE' to email me).

• Papers in Preparation 
  • Misc. Papers
  • Book Reviews
  • Review Papers
  • Commentary and Critique
• Sites I Maintain
• Independent Study
• Academic Interests

Papers in Preparation 

Misc. Papers

The Computational Stance: This paper seeks to outline a fourth, computational, stance in addition to Dennett's three: physical, functional and intentional. The computational stance is the strategy of interpreting the behavior of a system (person, animal, artifact, or the like) by treating it as if it were a computational, that is, governed by algorithms or implementations of functions that are "computable", "tractable" and to complex computational systems (agents) "information bearing." There are several compelling reasons to adopt this stance, as well as some important criticisms.

Philosophy in Runtime: The process of encoding a thought experiment in a formal system is, itself, beneficial in the same way as standard conceptual analysis: hidden assumptions are unburied and seemingly simple ideas yield refined notions. But, in a way, encoding is more honest—the process is not satisfied until you reach a syntactic, algorithmic level of explicitness and, once our intuitions are encoded, further light may be cast during runtime. Will your thought experiment crash, loop endlessly, or churn away at intractable problems? Do your assumptions actually lead to your conclusions? Do they yield more than expected? Less? As any programmer knows, what we program to happen and what actually happens can be quite different.

Blockheads and other Brutes: Let's consider the larger set of agents I call Brutes. Brutes use any or all algorithms that are foreign to ours, or are, in general, unappealing in their processes. This can be in the form of look-up tables, randomized answers, Liebnizian monsters that have monadic processes that never talk to one-another or receive any input, etc. However, Brutes, by fiat pass the Turing test. Now suppose after a neuro-imaging breakthrough we discover some percentage of the population utilizes some abhorrent algorithms in their thinking. Are we to then discount them as being mere Brutes, not truly thinking, feeling people? To do so would be ridiculous. Now suppose that some percentage of the population use nothing but abhorrent algorithms. Can we dismiss them? Again, I do not think so. To maintain otherwise seems to me to be a result of arbitrary algorithmic chauvinism or finding consciousness and intelligence to be an essence that exists apart from function—the same intuition that allows philosophers to take zombie arguments seriously and succumb to the quagmire of privileged access.

Computational Philosophy: A Proposal: Computational philosophy (CP) is a philosophical sub-discipline, which uses computers as a subject matter, intuition pump, and research tool. Correspondingly, CP may be viewed as being comprised of three primary divisions Philosophy of Computation and Information, Computational Philosophy (proper) and Philosophical Modeling. Philosophy of Computation and Information is concerned with the intelligibility, and significance of the central concepts of Computer Science. Computational Philosophy proper applies the formal and conceptual apparatus of computation and information to traditional philosophical problems. Philosophical Modeling is the practice of systematic formalization and simulation of philosophical assumptions so their implications may be more fully explored. The purpose of this paper is to clearly present the concepts, methods and problems that define Computational Philosophy as well as its appeal to philosophers, history, conceptual foundations, scope and critiques of CP itself.

Gettier Worlds: Reductio ad absurdam of the Gettier problem, showing the origin to be defining knowledge as being indefeasible.

The Frame Problem in the Background:

On Philosophical Constraints:

Nth Order Extensionalism:

Identity, Information and Invariance:

The Formal Properties of Representation:

Book Reviews

Blackwell's Guide to Philosophy of Information and Computation:

Review Papers

Models and Modes of Computation: When most people think of computers, naturally they think of their desktop PCs. Philosophers inherit this conception, which leads to some quarrels for those of us who wish to extend the notion of computation to natural processes. I wish to argue that computers are more common than most philosophers think, if not ubiquitous. I will start with the uncontroversial observation that integrated (non-programmable) computers are all around us in the form of watches, soda machines, automatic door openers, stoplights and so on. These are understood to be computers in that they lawfully change states; given certain inputs they return certain outputs. This is uncontravercial.

Moving on to natural objects, we may (borrowing from Dennett’s Darwin’s Dangerous Idea) look at the sand distribution on the beaches as the result of a sorting algorithm implemented by the waves of the ocean. The animals we see today (including ourselves) may be seen as answers (outputs) from an ever-changing blind optimization problem (evolution). Again, these processes lawfully change states and, given particular inputs, they return particular outputs. Conceived so generally, anything may be regarded as a computer—the object need not be man made.

Complex Systems for Philosophers: The study of Complex Systems has yielded many ideas that may be used (and abused) by philosophers. This paper surveys some of the most philosophically salient ideas.

Seven Algorithms Philosophers Should Know:

Commentary and Critique

Oracles, Supertasks, Hypercomputation and Other Fantasies:

ID Theory: Opening a Wedge Bit by Bit:

Sites

Computational Philosophy: Semi-proffesional promotional site.

Johnny Logic: Personal site--you are here!

Independent Study

Computational Philosophy: an annotated bibliography:

Computation and Information in Physical Systems: I propose that we survey computation and information in physical systems. The general subject matter includes neural networks, nonlinear dynamical systems, molecular computing, the physical limitations of computing and information, quantum computation, cellular automata, algorithmic information theory, complex adaptive systems and Maxwell’s demon. We may pursue any of topics of common interest to any desired level of depth and this document will change accordingly.

Cognitive Neuropsychology: Cognitive neuroscience is the science of the psychological, computational, and neuroscientific bases of cognition, perception, action, memory, language, and selective attention. We will familiarize ourselves with the historical development of cognitive neuroscience, learn about the functional organization of the brain, while focusing the biological underpinnings of mind and mental processes.

Academic Interests

Though I can only claim competence in a few of these subjects, I find them all exciting.