Many different architectures have been proposed for the design of autonomous agents. In this article, the application of the belief-desire-intention architecture to the artificial soccer domain is described. We show how it supports efficient deliberation in a highly dynamic environment.

Modeling various aspects of language-syntax, semantics, pragmatics, and discourse, among others -- by the use of constrained formal-computational systems, just adequate for such modeling, has proved to be an effective research strategy, leading to deep understanding of these aspects, with implications for both machine processing and human processing. This approach enables one to distinguish between the universal and stipulative constraints. This is in contrast to an approach where we start with the most powerful formal-computational system and then model the phenomena by making all constraints stipulative in a sense. The use of constrained systems for modeling leads to some novel ways of describing locality of structures and brings out the relationship between the complexity of description of primitives and local computations over them. These ideas serve to unify theoretical, computational, and statistical aspects of natural language processing in AI. It is expected that this approach will also be productive in other domains of AI.

I'm Not in Love (or Love's Labours Lost) A program cannot know what it is like to fall in love (See "Being and Lovingness," ed. Your claim that it would be "irresponsible" to show me the contents of your alleged Date: Wed, 19 Aug 2021 Kbase is a crude evasion of academic honesty. To: Lovecraft@ruth-whitehouse.com Your claim to have "perfect understanding" of A. Argaiv From: argaiv@great-western.edu a subject as complex and elusive as human emotion is ridiculous. Please forward my original considered. Greek hexameters?? Try LyreLyre!! ] request to someone in your organization who According to a recent survey, your web service Dear Professor Argaiv: can answer it more responsibly.

In real life, such functions range of objects along with the perceptual might be useful for in-home care of the capabilities required to support it. The rules specified a fixed course and a fixed set This event was extremely difficult because it of objects that would populate it. The course forced teams to implement both manipulation consisted of typical household furniture and (the grasping and moving of objects) and visual Lexan partitions arranged to produce a simplified object recognition. The objects were typical required teams to implement them for a wide household objects, such as a television remote, range of objects. It therefore eliminated a a pill bottle, and fruits and vegetables.

Unlike other entrants that fashioned good softbot teams from a battery of relatively wellunderstood robotics techniques, our goal was to see if it was even possible to use evolutionary computation to develop high-level soccer behaviors that were competitive with the human-crafted strategies of other teams. "Everyone Go after the Ball": A Popular but in a domain such as robot soccer. Our approach was to evolve a population of teams of Lisp s-expression algorithms, evaluating each team by attaching its algorithms to robot players and trying them out in the simulator. Early experiments tested individual players, but ultimately, the final runs pitted whole teams against each other using coevolution. After evaluation, a team's fitness assessment was based on its success relative to its opponent.

Researchers and technology developers from the National Aeronautics and Space Administration (NASA), other government agencies, academia, and industry recently met in Pasadena, California, to take stock of past and current work and future challenges in the application of AI to highly autonomous systems. The meeting was catalyzed by new opportunities in developing autonomous spacecraft for NASA and was in part a celebration of the fictional birth year of the HAL-9000 computer.

Points were awarded for picking up objects of a specific type (ball, cube, or moving squiggle ball) and specific color (figure 2). Penalty points were deducted for he Mars Pathfinder Mission, featuring for the Find-Life-on-Mars event. The general colliding with rocks, placing an object in the concept was to have the robots locate, collect, wrong door, and traveling within the danger and deliver a variety of "life forms," zones. We also specified penalties for modifying including both stationary and moving objects. the lander, although no group took advantage Technically, the event was designed to highlight of this option. No other modification of mobile manipulation, object recognition, the environment was allowed.

The Association for the Advancement of Artificial Intelligence Spring Symposium on Interactive and Mixed-Initiative Decision-Theoretic Systems was held at Stanford University from 23-25 March 1998. The symposium attracted approximately 30 researchers from around the world. Topics discussed included incremental model construction, user interaction, explanation generation, and applications.

Robotic soccer is a challenging research domain that involves multiple agents that need to collaborate in an adversarial environment to achieve specific objectives. In this article, we describe CMUNITED, the team of small robotic agents that we developed to enter the RoboCup-97 competition. We designed and built the robotic agents, devised the appropriate vision algorithm, and developed and implemented algorithms for strategic collaboration between the robots in an uncertain and dynamic environment. The robots can organize themselves in formations, hold specific roles, and pursue their goals. In game situations, they have demonstrated their collaborative behaviors on multiple occasions. We present an overview of the vision-processing algorithm that successfully tracks multiple moving objects and predicts trajectories. The article then focuses on the agent behaviors, ranging from low-level individual behaviors to coordinated, strategic team behaviors. CMUNITED won the RoboCup-97 small-robot competition at the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan.

The object-recognition module that was nonmanipulator category. In the last days before the finals, the students heavily modified or replaced. For example, during the types of object that were in the actual environment. Once pixels to modify their subsystems). It is fair to say the competition served to and a flag ground-plane assumption.