A survey on the design of multiprocessing systems for artificial intelligence applications
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Title: A Survey on the Design of Multiprocessing Systems for Artificial Intelligence Applications

Section 1: Characteristics of AI Computations
Description 1: Discuss the unique requirements of AI computations, including symbolic processing, nondeterministic computations, dynamic execution, potential for parallel and distributed processing, knowledge management, and open systems.

Section 2: Heuristic Searches
Description 2: Explain the importance of heuristic searches in AI computations and how heuristic knowledge is used to guide the search process to improve efficiency.

Section 3: Faster Technologies and Parallel Processing
Description 3: Review the technological advancements and parallel processing strategies that can enhance the computational efficiency of AI systems.

Section 4: Design Issues of Parallel AI Architectures
Description 4: Explore the representation level, control level, and processor level design issues for AI computer systems and discuss the development processes and challenges at each level.

Section 5: Representation Level
Description 5: Cover the knowledge-representation schemes, domain knowledge representations, metaknowledge representations, and AI languages and programming paradigms.

Section 6: Consistency Maintenance
Description 6: Address the consistency maintenance issues in AI systems and non-monotonic reasoning to manage dynamic and incomplete knowledge.

Section 7: Partitioning
Description 7: Discuss strategies and methodologies for partitioning AI problems to exploit parallelism effectively.

Section 8: Synchronization
Description 8: Review the synchronization techniques necessary to ensure the correct execution of parallel AI programs, including shared memory and message-passing mechanisms.

Section 9: Scheduling
Description 9: Investigate static and dynamic scheduling strategies that allocate tasks to processors efficiently, considering dependencies and heuristic information.

Section 10: Processor Level
Description 10: Describe the microlevel architectures and macrolevel architectures, focusing on supporting basic AI operations and managing data efficiently.

Section 11: Functional-Programming-Oriented System-Level Architectures
Description 11: Provide an overview of architectures designed to support functional programming languages and manage data structures, particularly in functional and list-oriented computing environments.

Section 12: Logic-Programming-Oriented System-Level Architectures
Description 12: Explain the architectures supporting logic programming, such as Prolog machines, and their features and performance considerations.

Section 13: Semantic-Net and Distributed-Problem-Solving Architectures
Description 13: Discuss architectures for processing semantic networks and distributed problem-solving systems, including models like NETL and the Connection Machine.

Section 14: Hybrid Systems
Description 14: Explore the combination of different AI languages in hybrid systems and the integration of multiple paradigms for comprehensive AI processing.

Section 15: Fifth Generation Computer Projects
Description 15: Review the objectives, current progress, and future directions of the Japanese FGCS project and similar initiatives in other countries.

Section 16: Design Decisions of AI-Oriented Computers
Description 16: Summarize the top-down, bottom-up, and middle-out design approaches for AI computers, emphasizing the importance of understanding problem requirements and iterative design processes.

Section 17: Conclusion
Description 17: Conclude the survey by emphasizing the need for better AI algorithms, software management methods, and architectures to support efficient AI processing and highlight the complexity and challenges faced in AI system design.