Symbolic methods used in conventional AI: knowledge representation, search strategies, inference mechanisms in expert system shells. Neural network methods: system identification and pattern recognition issues, basic paradigms and their promises and limitation. Unified approaches using both symbolic and neural network methods. Implementation issues using microcomputers in specific application domains, e.g., adaptive control and microprocessor systems.