Artificial Intelligence Mccarthy (2007) States

Artificial Intelligence

McCarthy (2007) states intelligence is "...the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines." (McCarthy, 2007) Artificial Intelligence often referred to as 'AI' is stated to be "...the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable." (McCarthy, 2007) Arthur R. Jensen is stated by McCarthy to have stated of human intelligence the suggestion "...as a heuristic hypothesis' that all normal humans have the same intellectual mechanisms and that differences in intelligence are related to 'quantitative biochemical and physiological conditions. I see them as speed, short-term memory, and the ability to form accurate and retrievable long-term memories." (McCarthy, 2007) McCarthy states that this may or may not be true in regards to the intelligence of human beings however, "the situation in AI today is the reverse." (McCarthy, 2007) This is stated to be due to the speed, memory, and abilities of the computer programs in corresponding to the "intellectual mechanisms that program designers understand well enough to put in programs." (McCarthy, 2007)

I. CONCEPTION of NON-BIOLOGICAL INTELLIGENT MACHINE

The work of Alan Turing (1950) 'Computing Machinery and Intelligence' is stated to have examined and discussed conditions that would necessarily be considerations in the conception of an intelligent machine. Turing held that "...if the machine could successfully pretend to be human to a knowledgeable observer then you should certainly consider it intelligent, but a machine could still be considered intelligent without knowing enough about humans to imitate a human." (McCarthy, 2007) the work of Dennett (1998) 'Brainchildren' examines the Turing test and findings are stated that the AI while having human-level intelligence" are really the focus of an effort "to make computer programs that can solve problems and achieve goals in the world as well as humans." (McCarthy, 2007) the conception of a non-biological intelligent machine is held by John Searle to be "incoherent'.

II. GRAPHICAL METHODS for REPRESENTING CONCEPTUAL SYSTEMS

The first textbook on formal concept analysis was written by Jair Abe (2006) and is of the nature that makes the provision of a "systematic presentation of mathematical foundations and their relations to applications in computer science, especially in data analysis and knowledge processing." (Abe, 2006) Abe's work "presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge." (Abe, 2006) Abe states that theory and graphical representation are "closely coupled together." (Abe, 2006)

The work of Steels (2003) entitled: "Intelligence with Representation" relates that early cybernetics work has historically inspired 'behavior-based robotics" and that it "emphasizes that intelligence can be achieved without the kinds of representations common in symbolic AI systems. The paper argues that such representations might indeed not be needed for many aspects of sensory-motor intelligence but become a crucial issue when bootstrapping to higher levels of cognition. It proposes a scenario in the form of evolutionary language games by which embodied agents develop situated grounded representations adapted to their needs and the conventions emerging in the population." (Steels, 2003)

III. EMOTIONAL MECHANISM & EPISODIC LEARNING in a COGNITIVE AGENT

The work of Faghihi, et al. (2009) entitled: "How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent" reports having proposed the CTS (Conscious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions. This agent is capable of learning and remembering events and any related information such as corresponding procedures, stimuli and their emotional valences." (Faghihi, et al., 2009)

Faghihi et al. (2009) states additionally that the proposed "...episodic memory and episodic learning mechanism are closer to the current multiple-trace theory in neuroscience, because they are inspired by it contrary to other mechanisms that are incorporated in cognitive agents. This is because in our model emotions play a role in the encoding and remembering of events. This allows the agent to improve its behavior by remembering previously selected behaviors which are influenced by its emotional mechanism. Moreover, the architecture incorporates a realistic memory consolidation process based on a data mining algorithm." (Faghihi, et al., 2009)

IV. APPLICATIONS of AI

Applications of Artificial Intelligence include those as follows:

game playing;

speech recognition;

understanding natural language;

expert systems' and heuristic classification. (McCarthy, 2007)

V. REALITY of ROBOTIC PROGRAMMING - REAL-LIFE APPLICATIONS & USE

The work entitled: "Robotic Programming: A Practical Guide to Behavior-Based Robotics" disseminates the necessary skills for robot programming and effectively "deconstructs robot control into simple and distinct behaviors that are easy to program and debug for inexpensive microcontrollers with little memory." (nd) Applications include:

1) Demonstration of a system that integrates explanation, code examples and exercises using an online robot simulator;

2) Demonstrates programming for mobile robots;

3) Provides the tools to combine multiple sensors;

4) Demonstrates how to develop new robot behaviors by manipulating old ones and making adjustment to parameters in programming;

5) Provides examples of programming for object-seeking; object-avoidance; decision-making, etc.;

6) Leads to advanced strategies for design of behavior-based systems from scratch;

7) Introduces behavior-based programming historically and theoretically; and 8) Requires no background in programming or robotics. (Robotics and Artificial Intelligence, (RIA); nd)

Today's Artificial Intelligence programs and robots are becoming increasingly more diverse and include such advances as:

1) linking mobile robot performances with the environment using system maps as reported in the work of Held, Lampe, and Chatila (nd).

2) Another example is reported in the work of Menezes, Lerasle, and Dias (nd) 'Data Fusion for 3D Gestures Tracking Using a Camera Mounted on Robot."

3) the study of Pettre, et al. (nd) relates robotic capabilities in crowd navigation, scalable simulation and rendering' and the list goes on of the capabilities that are being designed into robots both in the present and projected designs for the future; and 4) Present initiatives include attempts to synthesize and model human locomotion using system identification such as the study of Suleiman, Monin and Laumond (nd) as well as programming that is specifically for robotic service provided to individuals in a sitting position and in the context of the robot helping or assisting the human. (Robotics and Artificial Intelligence, (RIA); nd)

VI. DISCUSSION & CONCLUSION