A versatile assembly system, using TV cameras and oomputer-controlled arm and moving table, is described. It makes almple assemblies such aa a peg and rings and a toy car. It separates parts from a heap, recognising them with an overhead camera, then assembles them by feel. It can be instructed to perform a new task with different parte by spending an hour showing it the parts and a day or two programming the assembly manipulations. A hierarchical description of parts, views, outlines etc. is used to construct models, and a structure matching algorithm is used in recognition.Later version appearing in Artificial Intelligence, Vol 6, pp. 129(1975) (available for a fee).In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

This paper presents a framework for characterizing automatic programming systems in terms of how a task is communicated to the system, the method and time at which the system acquires the knowledge to perform the task, and the characteristics of the resulting program to perform that task. It describes one approach In which both tasks and knowledge about the task domain are stated in natural language In the terms of that domain. All knowledge of computer science necessary to implement the task is internalized inside the system.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California, pp.494-499

A problem domain can be represented as a hierarchy of abstraction spaces in which successively finer levels of detail are introduced. The problem solver ABSTRIPS, a modification of STRIPS, can define an abstraction space hierarchy from the STRIPS representation of a problem domain, and it can utilize the hierarchy in solving problems. Examples of the system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides. Then some further Implications of the hierarchical planning approach are explored.Later journal article in Artificial Intelligence 5:115-135 (1974). Available for a fee. In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

The design of application of artificia l intelli­gence to a scientific task such as Organic Chemical Synthesis was the topic of a Doctoral Thesis completed in the summer of 197I. Chemical synthesis in practice involves i) the choice of molecule to be synthesized; i i) the formulation and specification of a plan for synthesis (involving a valid reaction pathway leading from commercial or readily available compounds to the target compounds with consideration of feasibility regarding the purposes of synthesis);iii ) the selection of specific individual steps of reaction and their temporal ordering for execution; iv) the exper­imental execution of the synthesis and v) the redesign of syntheses, if necessary, depending upon the exper­imental results. In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

"A program that achieves the interpretation of line drawings as polyhedral scenes is described. The method is based on general coherence rules that the surfaces and edges must satisfy, thereby avoiding the use of predetermined interpretations of particular categories of picture junctions and corners." The paper also comments on the relationship of this program to four other scene analysis programs.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California. Revised version in Artificial Intelligence 4:121-137.

In IJCAI-73, pp. 1–11.

Abduction is a basic form of logical inference, which is said to engender the use of plans, perceptual models, intuitions, and analogical reasoning - all aspects of Intelligent behavior that have so far failed to find representation in existing formal deductive systems. This paper explores the abductive reasoning process and develops a model for it s mechanization, .which consists of an embedding of deductive logic in an iterative hypothesis and test procedure. An application of the method to the problem of medical diagnosis is discussed.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

IJCAI-73, pp. 344–351

The paper deals with the problem of development the multilevel control algorithms fo r six-legged automatic walker, which provide the walker with the possibility to analyse the terrain profile before it while moving over rough terrain , and to synthesize adequate, rather reasonable kinematics of body and legs for walker's locomotion along the route and climbing over obstacles on it s way. DC simulation and analysis of walker's model moving image on DC display screen make it possible to evaluate the algorithms developed and to find ways for their improvement.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.

This paper proposes a modular ACTOR architecture and definitional method for artificial intelligence that is conceptually based on a single kind of object: actors [or, if you will, virtual processors, activation frames, or streams]. The formalism makes no presuppositions about the representation of primitive data structures and control structures. Such structures can be programmed, micro-coded, or hard wired 1n a uniform modular fashion. In fact it is impossible to determine whether a given object is "really" represented as a list, a vector, a hash table, a function, or a process. The architecture will efficiently run the coming generation of PLANNER-like artificial intelligence languages including those requiring a high degree of parallelism. The efficiency is gained without loss of programming generality because it only makes certain actors more efficient; it does not change their behavioral characteristics. The architecture is general with respect to control structure and does not have or need goto, interrupt, or semaphore primitives. The formalism achieves the goals that the disallowed constructs are intended to achieve by other more structured methods.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California.