The Computational Theory of Mind

computational description that could be physically implemented in diverse ways (e.g. through silicon chips, or neurons, or pulleys and levers). CCTM holds that a suitable abstract computational model offers a literally true description of core mental processes. It is common to summarize CCTM through the slogan “the mind is a Turing machine.” This slogan is also somewhat misleading, because no one regards Turing’s precise formalism as a plausible model of mental activity. The formalism seems too restrictive in several ways: Turing machines execute pure symbolic computation. The inputs and outputs are symbols inscribed in memory locations. In contrast, the mind receives sensory input (e.g. retinal stimulations) and produces motor output (e.g. muscle activations). A complete theory must describe how mental computation interfaces with sensory inputs and motor outputs. A Turing machine has infinite discrete memory capacity. Ordinary biological systems have finite memory capacity. A plausible psychological model must replace the infinite memory store with a large but finite memory store Modern computers have random access memory: addressable memory locations that the central processor can directly access. Turing machine memory is not addressable. The central processor can access a location only by sequentially accessing intermediate locations. Computation without addressable memory is hopelessly inefficient. For that reason, C. R. Gallistel and Adam King (2009) argue that addressable memory gives a better model of the mind than non-addressable memory. A Turing machine has a central processor that operates serially, executing one instruction at a time. Other computational formalisms relax this assumption, allowing multiple processing units that operate in parallel. Classical computationalists can