Physical Intelligence (2009)
A screenshot of the DARPA-funded 2009 physical intelligence project, the premise that a thermodynamics-based type of artificial intelligence can be built, that evolves. [5]
In human thermodynamics, physical intelligence, abbreviation PI, is a theory, premise, or research program, conceived by DARPA program manager Todd Hylton in 2009, which supposes that intelligence spontaneously evolves as a consequence of thermodynamics in open systems, and that such types of evolved intelligences can be built from chemical and electrical components. [1] A 2012 description of the so-called physical intelligence program, according to program manager Jamil R. Abo-Shaeer, is as follows: [6]

“The physical intelligence program will address its overall objective through a coordinated effort in three complementary domains: theory, implementation, and analysis. The objective of the theory domain is to develop and validate a physical formalism that unifies and expands ideas from diverse domains such as evolution, thermodynamics, information, and computation. The objective of the implementation domain is to demonstrate the first human-engineered open thermodynamic systems that spontaneously evolve nontrivial "intelligent" behavior under thermodynamic pressure from their environment. The objective of the analysis domain is to develop analytical tools to support the development of human-engineered physically intelligent systems and to understand physical intelligence in the natural world.”

As of early 2013, however, to note, the funding for the program has since been exhausted. [7]

The idea of PI was conceived as a two-year research and development project, initiated by Defense Advanced Research Projects Agency (DARPA), of the US Department of Defense, particularly through the efforts of DARPA program manager Todd Hylton in May of 2009. [1] According to the 30-page project proposal publication, the project of constructing or understanding "physical intelligence" is described as a follows:
Physical Intelligence (diagram)
A flowchart diagram of the physical intelligence model. [6]

Synopsis: Our current understanding of the natural world lacks an effective description of the evolution of complexity evident in all living systems. The Physical Intelligence (PI) program hypothesizes that a unifying description called physical intelligence can be developed from currently fragmented disciplinary domains. The vision of the Physical Intelligence program is to develop a physically-grounded understanding of intelligence that applies to engineered systems and scales to high levels of organization. If achieved, this understanding might be applied to problems as diverse as the complexity of living systems, the nature of human intelligence, and the engineering of systems that spontaneously evolve intelligent behavior. This capability would find broad utility in the many defense systems requiring improved autonomy in unmanned systems and improved situational awareness and decision support in manned systems.

Background: For the past 50 years, the dominant paradigm for intelligence supposes that the brain is the seat of intelligence and is functionally equivalent to a computer capable of executing any algorithm. Hence, the current conceptual foundations of intelligence are rooted in the abstractions of logic. Although many valuable and practical applications have emerged from this approach, the goal of true machine intelligence remains distant and the validity of the conceptual foundation is unclear. In contrast, our understanding of the evolution of life is rooted primarily in observations of the natural world, resulting in a multitude of descriptive, domain-specific models of evolutionary processes. A particular challenge is the specification of the mechanisms of selection, as they are typically attributed to a complex environment within which a model system is situated. With some exceptions, current approaches to understanding intelligence and evolution are disconnected and often lack grounding in fundamental physical principles.
Physical intelligence (diagram 2)
A physical intelligence project overview schematic. [6]

The Physical Intelligence program supposes that the phenomena associated with intelligence and evolution can be understood as natural consequences of complex, open thermodynamic systems. In particular, evolutionary variation may result from thermodynamic fluctuations, and evolutionary selection may result from entropy production. Further, the hierarchy of organization observed in the natural world may result from the evolutionary/thermodynamic growth of “networks” of energy transduction mechanisms. These networks include neural systems, for example, but also many other complex natural systems. Although the idea that life is “a struggle for entropy” (Boltzmann) has been supposed for more than a century, acknowledged formalisms, validation in the natural world, and applications to engineered systems are scarce. The Physical Intelligence program aspires to change this situation.

Description: The outline of the program is hinged on three independent but connected points: (a) Creating a theory (a mathematical formalism) and validating it in natural and engineered systems; (b) Building the first human-engineered systems that display physical intelligence in the form of abiotic, self-organizing electronic and chemical systems; (c) Developing analytical tools to support the design and understanding of physically intelligent systems.

The outline of the theory seems to be similar to the concept of artificial intelligence (AI), a term coined by American computer scientist John McCarthy in 1959, defined as the science and engineering of making intelligent machines, albeit with the exception of the requirement of electrical parts and chemical parts, rather than computer parts alone. [2]

Historical theories
See main: Neumann automaton theory
The theory of electrical-chemical intelligent systems, to note, was first proposed by American chemical engineer John Neumann in 1948, who envisaged a robot or automaton, made of wires, electrical motors, batteries, etc., constructed in such a way that when floating on a lake stoked with component parts, it will reproduce itself (self-replicate), albeit only if a source of free energy is available. [3]

A similar theory was proposed in 1965 by Canadian materials science engineer Jack Kirkaldy, who argued that the “human brain may be regarded as an irreversible system which is constrained by a fixed inflow of free energy in the form of chemical nourishment from within the body and information from the environment.” [4]

The only other possible theories available may come from the work of Norbert Wiener (cybernetics), Ilya Prigogine (dissipative structures), possibly recent complexity theory work, or other neuroscience possibilities (e.g. neurochemical thermodynamics, neurothermodynamics, neurodynamics, etc.).

1. (a) Physical Intelligence (PI) – DARPA-BAA-09-63 –
(b) DARPA – Wikipedia.
2. Artificial intelligence – Wikipedia.
3. (a) Neumann, John von. (1963). "Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components", in Collected Works (A. Taub editor), Vol. 5, pgs. 341-47. MacMillian, New York.
(b) Neumann, John von. (1966). Theory of Self-Replicating Automata, A. Burks, ed. University of Illinois Press.
4. Kirkaldy, J.S. (1965). "Thermodynamics of the Human Brain" (PDF), Biophys J. Nov. 5(6): 981-986.
5. Physical Intelligence (Archived) –
6. Physical Intelligence –
7. Email communication from Jamil R. Abo-Shaeer to Libb Thims (26 Feb 2013).

Further reading
● Drummond, Katie. (2009). “Darpa: Heat + Energy = Brains. Now Make Us Some.” Wired, May 08.
● Uexkull, Jakob and Oneil, Joseph D. (2010). A Foray Into the World of Animals and Humans: With a Theory of Meaning (pg. 249). University of Minnesota Press.

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