@article {15956,
	title = {A logic-based model of intention formation and action for multi-agent subcontracting},
	journal = {Artificial Intelligence},
	volume = {163},
	year = {2005},
	month = {2005/04//},
	pages = {163 - 201},
	abstract = {We present a formalism for representing the formation of intentions by agents engaged in cooperative activity. We use a syntactic approach presenting a formal logical calculus that can be regarded as a meta-logic that describes the reasoning and activities of the agents. Our central focus is on the evolving intentions of agents over time, and the conditions under which an agent can adopt and maintain an intention. In particular, the reasoning time and the time taken to subcontract are modeled explicitly in the logic. We axiomatize the concept of agent interactions in the meta-language, show that the meta-theory is consistent and describe the unique intended model of the meta-theory. In this context we deal both with subcontracting between agents and the presence of multiple recipes, that is, multiple ways of accomplishing tasks. We show that under various initial conditions and known facts about agent beliefs and abilities, the meta-theory representation yields good results.},
	keywords = {Cooperative agents, intentions, Minimal model semantics, Subcontracting, Syntactic logic},
	isbn = {0004-3702},
	doi = {16/j.artint.2004.11.003},
	url = {http://www.sciencedirect.com/science/article/pii/S0004370204001924},
	author = {Grant,John and Kraus,Sarit and Perlis, Don}
}
@conference {11960,
	title = {Purposive and qualitative active vision},
	booktitle = {Proceedings of 10th International Conference on Pattern Recognition, 1990},
	volume = {i},
	year = {1990},
	month = {1990/06/16/21},
	pages = {346-360 vol.1 - 346-360 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The traditional view of the problem of computer vision as a recovery problem is questioned, and the paradigm of purposive-qualitative vision is offered as an alternative. This paradigm considers vision as a general recognition problem (recognition of objects, patterns or situations). To demonstrate the usefulness of the framework, the design of the Medusa of CVL is described. It is noted that this machine can perform complex visual tasks without reconstructing the world. If it is provided with intentions, knowledge of the environment, and planning capabilities, it can perform highly sophisticated navigational tasks. It is explained why the traditional structure from motion problem cannot be solved in some cases and why there is reason to be pessimistic about the optimal performance of a structure from motion module. New directions for future research on this problem in the recovery paradigm, e.g., research on stability or robustness, are suggested},
	keywords = {active vision, Automation, brain models, complex visual tasks, Computer vision, environmental knowledge, highly sophisticated navigational tasks, HUMANS, Image reconstruction, intentions, Kinetic theory, Laboratories, Medusa, Motion analysis, Navigation, planning, planning (artificial intelligence), purposive-qualitative vision, recovery problem, Robust stability, Robustness, SHAPE, stability},
	isbn = {0-8186-2062-5},
	doi = {10.1109/ICPR.1990.118128},
	author = {Aloimonos, J.}
}
