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Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is each interpretation of the existing data? What additional information would the best interpretations make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. (Kripke semantics defies statistics in a big way.) But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is each interpretation of the existing data? What additional information would the best interpretations make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is each interpretation of the existing data? What additional information would the best interpretations make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. (Kripke semantics defies statistics in a big way.) But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

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Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is thiseach interpretation of the existing data? What additional information would that interpretationthe best interpretations make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is this interpretation of the existing data? What additional information would that interpretation make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is each interpretation of the existing data? What additional information would the best interpretations make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

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Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is this interpretation of the existing data? What additional information would that interpretation make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively driven-driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is this interpretation of the existing data? What additional information would that interpretation make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively driven behavior and provide some of the motivations involved.

Modal logic captures meaning beyond clearly statable facts. It often reflects possibility, desirability, clarity, plausibility or some other sought goal (and simultaneously the restrictions on pursuing that goal), the kind of knowledge that someone has about what they are saying, that cannot be embedded meaningfully in the statement of the fact itself, but can only be alluded to.

You can think of the kinds of deductions made in expert systems as modal logic. "How possible and how definitive is this interpretation of the existing data? What additional information would that interpretation make most relevant? So that is what I will ask next." is the standard step in a medical diagnosis system or a trend-recognition system.

But "Possible", "definitive", and "relevant" here, are modal concepts. They are about propositions. They limit reasonable interpretation without having much effect on the full range of interpretations. And they very hard to quantify or collect data on, or to combine given data about, reliably. So they call for something less that statistics and something more than formal logic.

Since goal-seeking systems that are not sheer numerical optimizations seem like a good way of addressing many problems with a computer, much of 'AI', from medical diagnosis simplification to good game character psychology, can be formulated as a rated modal logic.

The basic approaches to modal logic within philosophy do not get the right kind of attention to really develop into useful expert deduction systems. The intended semantics are different, and the common models immediately flee far from tractability. But the ideas of modal logic do form the basis of interpreting subjectively-driven behavior and provide some of the motivations involved.

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