Introduction to AI
... •At least 2 Lab Assignments where attendance will be compulsory and will be taken. •Critical reviews of interesting papers •Take Home/In class Assignments (LISP/PROLOG) CS 531: Dr M M Awais (LUMS) ...
... •At least 2 Lab Assignments where attendance will be compulsory and will be taken. •Critical reviews of interesting papers •Take Home/In class Assignments (LISP/PROLOG) CS 531: Dr M M Awais (LUMS) ...
Conventional Ratio and Artificial Intelligence (AI) Diagnostic methods for DGA in Electrical Transformers
... the use of artificial intelligence techniques to assist the DGA. These investigations include the expert system approach, fuzzy system approach and the artificial neural network (ANN) approach [9]. The basic idea of neural network based fault diagnosis is nonlinear mapping [8]. It is assumed that th ...
... the use of artificial intelligence techniques to assist the DGA. These investigations include the expert system approach, fuzzy system approach and the artificial neural network (ANN) approach [9]. The basic idea of neural network based fault diagnosis is nonlinear mapping [8]. It is assumed that th ...
When to Use Expert Systems
... Principles and Learning Objectives • Artificial intelligence systems form a broad and diverse set of systems that can replicate human decision making for certain types of well-defined problems. – Define the term artificial intelligence and state the objective of developing artificial intelligence s ...
... Principles and Learning Objectives • Artificial intelligence systems form a broad and diverse set of systems that can replicate human decision making for certain types of well-defined problems. – Define the term artificial intelligence and state the objective of developing artificial intelligence s ...
For Review Only - Portsmouth Research Portal
... groups of attributes uniquely shared by examples in given classes and forms rules with the IF part as conjunctions of those attributes and the THEN part as the classes. The program removes correctly classified examples from consideration and stops when rules have been formed to classify all examples ...
... groups of attributes uniquely shared by examples in given classes and forms rules with the IF part as conjunctions of those attributes and the THEN part as the classes. The program removes correctly classified examples from consideration and stops when rules have been formed to classify all examples ...
WORD - Semiosis Evolution Energy
... Whether Skagestad was the first to distinguish explicitly between Artificial Intelligence (AI) and Intelligence Augmentation (IA) in just these terms, treating it as a formal distinction, I do not know. The distinction itself can be said to have existed in some sense as far back as 1962 (if not earl ...
... Whether Skagestad was the first to distinguish explicitly between Artificial Intelligence (AI) and Intelligence Augmentation (IA) in just these terms, treating it as a formal distinction, I do not know. The distinction itself can be said to have existed in some sense as far back as 1962 (if not earl ...
artificial intelligence
... knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence ...
... knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence ...
Fuzzy-probabilistic logic for common sense
... They include, but not exhaustively: [18]’s Markov Logic Networks which is based on Markov random fields instead of Bayesian networks; and Loopy Logic which is based on [16]’s belief propagation algorithm; [3]’s Probabilistic Relational Models; and [10]’s Bayesian Logic Programs. Relatedly, [17] deve ...
... They include, but not exhaustively: [18]’s Markov Logic Networks which is based on Markov random fields instead of Bayesian networks; and Loopy Logic which is based on [16]’s belief propagation algorithm; [3]’s Probabilistic Relational Models; and [10]’s Bayesian Logic Programs. Relatedly, [17] deve ...
without teaching statement
... Microsoft Research, Redmond, WA, U.S.A. Supervisor: Dr. John Manferdelli, Anti-Piracy Group Worked on Digital Rights Management; designed methods that use control- and data-flow analysis on binary program code to embed hard-to-break license authentication protocols in arbitrary programs. Intern, Vis ...
... Microsoft Research, Redmond, WA, U.S.A. Supervisor: Dr. John Manferdelli, Anti-Piracy Group Worked on Digital Rights Management; designed methods that use control- and data-flow analysis on binary program code to embed hard-to-break license authentication protocols in arbitrary programs. Intern, Vis ...
now
... optimal actions. An example of this is the Google DeepMind-developed machine learning-driven game player AlphaGo, which made headlines last year for being the first machine to beat the best human at the game of Go, a game that is significantly more challenging than chess. The applications of machine ...
... optimal actions. An example of this is the Google DeepMind-developed machine learning-driven game player AlphaGo, which made headlines last year for being the first machine to beat the best human at the game of Go, a game that is significantly more challenging than chess. The applications of machine ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
The Behavior-Oriented Design of Modular Agent Intelligence
... 2. reactive planning, the ordering of expressed actions via carefully specified program structures, and 3. (optionally) deliberative planning, which may inform or create new reactive plans, or, in principle, even learn new behaviors. In this section I will discuss these systems and their history in ...
... 2. reactive planning, the ordering of expressed actions via carefully specified program structures, and 3. (optionally) deliberative planning, which may inform or create new reactive plans, or, in principle, even learn new behaviors. In this section I will discuss these systems and their history in ...
ppt
... Systems that think rationally it possible to perceive, reason, and act'' (Winston, 1992) ...
... Systems that think rationally it possible to perceive, reason, and act'' (Winston, 1992) ...
Planning for a Mobile Robot to Attend a Conference
... been developing a planning system to be integrated with the basic robot behaviorproducing modules to recommend tasks the robot should be working on at a given point of execution. Planning problems we are dealing with involve metric time constraints (e.g., the robot has to be on time for it presentat ...
... been developing a planning system to be integrated with the basic robot behaviorproducing modules to recommend tasks the robot should be working on at a given point of execution. Planning problems we are dealing with involve metric time constraints (e.g., the robot has to be on time for it presentat ...
Engineering Note
... sequence of states starting with the initial state and the planners responded to each state with an action based on the solution they found. 30 simulations were conducted for each problem. For goal-based problems success was measured by whether the goal was reached at the end of the simulation. For ...
... sequence of states starting with the initial state and the planners responded to each state with an action based on the solution they found. 30 simulations were conducted for each problem. For goal-based problems success was measured by whether the goal was reached at the end of the simulation. For ...
Building a Constraint Solver that Learns. In Proceedings of the AAAI
... game player, learned to play19 different two-dimensional, finite-board games as well or better than the best human experts (Epstein, 2001). Ariadne, a FORR-based pathfinder for two-dimensional mazes, learned to find its way efficiently through complex mazes modeled on real-world spaces (Epstein, 199 ...
... game player, learned to play19 different two-dimensional, finite-board games as well or better than the best human experts (Epstein, 2001). Ariadne, a FORR-based pathfinder for two-dimensional mazes, learned to find its way efficiently through complex mazes modeled on real-world spaces (Epstein, 199 ...
Ten Years of the AAAI Mobile Robot Competition and Exhibition
... world-class research (and the funding that goes with it) while balancing risk. The risk arises from the danger of setting the bar so high that no robot can complete the task. In the worst case, critics might interpret the failure of robots to complete the task as a systemic failure of AI robotics it ...
... world-class research (and the funding that goes with it) while balancing risk. The risk arises from the danger of setting the bar so high that no robot can complete the task. In the worst case, critics might interpret the failure of robots to complete the task as a systemic failure of AI robotics it ...
Leadership and Emotional Intelligence - WSU Tri
... Developing the next generation of corporate leaders is a key concern for HR executives today given the tenuous upturn in the economy and increasing departures of organizational leaders. In fact, after retaining and rewarding top employees, a 2012 Society for Human Resources Management survey found t ...
... Developing the next generation of corporate leaders is a key concern for HR executives today given the tenuous upturn in the economy and increasing departures of organizational leaders. In fact, after retaining and rewarding top employees, a 2012 Society for Human Resources Management survey found t ...
Vincent C. Müller Is There A Future For AI Without Representation?
... Bishop 2002; Searle 1980). This lack of ‘mental representation’ is considered fatal for the creation of an intelligent agent – on the standard assumption that perception, reasoning, goals and planning are based on representations and essential to cognition. At the same time, many technical problems ...
... Bishop 2002; Searle 1980). This lack of ‘mental representation’ is considered fatal for the creation of an intelligent agent – on the standard assumption that perception, reasoning, goals and planning are based on representations and essential to cognition. At the same time, many technical problems ...
Faculty of Arts Atkinson College
... In this chapter, we will study: What is meant by artificial intelligence How expert systems are developed and how they perform How AI has been applied to other arenas, such as natural language processing and neural computing The concept and usefulness of intelligent agents Ethical and leg ...
... In this chapter, we will study: What is meant by artificial intelligence How expert systems are developed and how they perform How AI has been applied to other arenas, such as natural language processing and neural computing The concept and usefulness of intelligent agents Ethical and leg ...
Artificial Intelligence
... a human being to come to harm. 2. A robot must obey the orders given it by human beings except where those orders would conflict with the First Law. 3. A robot must protect its own existence, except where such protection would conflict with the First or Second Law. • Three Laws were clear, direct, a ...
... a human being to come to harm. 2. A robot must obey the orders given it by human beings except where those orders would conflict with the First Law. 3. A robot must protect its own existence, except where such protection would conflict with the First or Second Law. • Three Laws were clear, direct, a ...
21. Reinforcement Learning (2001)
... On each trial, the system selects an action a(t) from its set of m actions according to a probability vector (p1(t),...,pm (t)), where pi(t) = Pr{a(t) = ai}. Learning rule: If action ai is chosen on trial t and the critic's feedback is 'success', then pi(t) is increased and the other probabilities a ...
... On each trial, the system selects an action a(t) from its set of m actions according to a probability vector (p1(t),...,pm (t)), where pi(t) = Pr{a(t) = ai}. Learning rule: If action ai is chosen on trial t and the critic's feedback is 'success', then pi(t) is increased and the other probabilities a ...
EXPERT SYSTEMS - THE NEW BUSINESS SIMULATION TOOL
... the export system to the user. Figure 2 illustrates the results of the consultation. In this case, two different strategies were plausible, with one, the Empirical model, showing a higher degree of confidence. Figure 3 shows the questions asked by the system of the user, this screen shows three ques ...
... the export system to the user. Figure 2 illustrates the results of the consultation. In this case, two different strategies were plausible, with one, the Empirical model, showing a higher degree of confidence. Figure 3 shows the questions asked by the system of the user, this screen shows three ques ...
SAT-based planning in complex domains: Concurrency, constraints
... goal state. This is the idea underlying planning as satisfiability in [26]. However, this is not always the case in our setting, where actions can be nondeterministic and there can be multiple initial states. For example, considering the planning problem (9), executing the possible plan consisting o ...
... goal state. This is the idea underlying planning as satisfiability in [26]. However, this is not always the case in our setting, where actions can be nondeterministic and there can be multiple initial states. For example, considering the planning problem (9), executing the possible plan consisting o ...
PDF - 1.4 MB - Massachusetts Institute of Technology
... start with a literal to "prove", which we call C. We will also use Green's trick (as in Chapter 6.3) to keep track of any variable bindings in C during the proof. We will keep a stack (first in, last out) of goals to be proved. We initialize the stack to have C (first) followed by the Answer literal ...
... start with a literal to "prove", which we call C. We will also use Green's trick (as in Chapter 6.3) to keep track of any variable bindings in C during the proof. We will keep a stack (first in, last out) of goals to be proved. We initialize the stack to have C (first) followed by the Answer literal ...
The SCHOLAR Legacy: A New Look at the Affordances of Semantic
... South America. To complicate matters further, in order to understand places as humans do, an agent must understand that places have attributes that, from a human perspective, provide certain affordances [Gibson, 1979; Glenberg & Robertson, 1999]. For example, a place can be safe, dangerous, hard to ...
... South America. To complicate matters further, in order to understand places as humans do, an agent must understand that places have attributes that, from a human perspective, provide certain affordances [Gibson, 1979; Glenberg & Robertson, 1999]. For example, a place can be safe, dangerous, hard to ...