IJCAI-97 was held August 23 - 29 in
Nagoya, Japan. 17 tutorials and 32 workshops from a
variety of AI areas were held in conjunction with IJCAI-97 and attracted many
participants, among others many Japanese participants.
IJCAI-97 was very interesting in terms
of its invited talks, the technical program, the
exhibition, and of course RoboCup-97 that magically attracted most of the IJCAI
participants. As usual and very useful, the invited talks provided an overview on what is
going on in particular areas of AI and they demonstrated the state-of-the-art in these
areas. To name just three of the overall twelve invited talks -- which does not include
any preference -- Margarete Boden gave a brilliant talk about creativity and Artificial
Intelligence, Wolfgang Bibel wanted to convince the AI-community that theorem proving is
well suited to tackle problems in many areas of AI, and Rich Sutton surveyed the recently
booming reinforcement learning.
Rightly so, the Computers and Thought
lecture by Leslie Kaebling "Why robby can't learn: the difficulty of learning in
autonomous agents'', the Research Excellence lecture by Aravind Joshi "Relationship
between natural language processing and AI'', and the awarded papers presentations of Lin
(Applications of the situation calculus to formalizing control and strategic information:
the Prolog Cut operator), Carbonell et al.(Translingual information retrieval: a
comparative evaluation), and Huang & Russell (Object Identification in a Bayesian
Context) got a lot of attention at IJCAI-97.
As for the technical program, I can
give my limited personal impression only because of the ususal parallel execution of the
program. My bias is towards planning, theorem proving, learning, and analogy and
case-based reasoning. Here, the planning and learning sessions were interesting in
general, theorem proving had little contributions, and analogy was rather unsatisfying. In
a planning session, e.g., Givan &Dean's paper reconstructed STRIPS planning in terms
of finite automata and translated model minimization into systematic regression.
Notably, computer-aided education,
neural networks, information retrieval, and vision got a new or revived appearance. For
the purpose of unifying the field again, this seems to be promising. Many contributions
came from natural language processing and distributed AI in this year's IJCAI. Less papers
than at former IJCAIs were presented in non-monotonic reasoning, automated reasoning in
general, and knowledge representation.
Universitat des Saarlandes,