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Introduction to Expert Systems
Published in Chris Nikolopoulos, Expert Systems, 1997
In propositional logic, logic formulas are constructed by combining true or false propositions with the basic logical operators of negation (¬), conjunction (∧), and disjunction ( ∨ ). A proposition is a statement having the value of either true or false. For example,
Evaluating Effects of Enhanced Autonomy Transparency on Trust, Dependence, and Human-Autonomy Team Performance over Time
Published in International Journal of Human–Computer Interaction, 2022
Ruikun Luo, Na Du, X. Jessie Yang
An intelligent assistant helps the participant by recommending where to go. The intelligent assistant is a knowledge-based agent and reasons using propositional logic (Russell & Norvig, 2010). Propositional logic is a mathematical model that reasons about the truth or falsehood of logical statements. By using logical inference, the agent will give the values of four logical statements for a given location (e.g. location D2): (1) there is a pit at this location, denoted as (2) there is no pit at this location, denoted as (3) there is a wumpus at this location, denoted as (4) there is no wumpus at this location, denoted as Based on the value of these 4 logical statements, we can categorize the location into one of the six different conditions shown in Figure 2: Y represents there is a pit/wumpus at this location (value of the first/third logical statements is true); N represents there is no pit/wumpus at this location (value of the second/fourth logical statement is true); NA represents the agent is not sure about the existence of pit/wumpus at this location (values of all the four statements are false). The shaded squares in Figure 2 are the impossible cases because the pit and wumpus cannot co-exist in one location. For each case in Figure 2, the agent will assign probabilities of encountering a wumpus, falling into a pit, finding a gold bar or nothing happens as well as the corresponding expected scores if the hunter moves to that location. The agent will randomly select one of the potential next locations with the highest expected score as the recommendation.
Morphologic for knowledge dynamics: revision, fusion and abduction
Published in Journal of Applied Non-Classical Logics, 2023
Isabelle Bloch, Jérôme Lang, Ramón Pino Pérez, Carlos Uzcátegui
Here propositional logic is considered, and propositional formulas are used to encode either pieces of knowledge (which may be generic, for instance integrity constraints, or factual such as observations), or subjective items such as beliefs or preferences. Such formulas are then used for complex reasoning or decision-making tasks.