AI News, Artificial Intelligence/Definition
- On Sunday, September 30, 2018
- By Read More
Over the past few years, you might have come across the term artificial intelligence and have imagined it to be a vivid personification of extraterrestrial beings or robots.
Over the course of this section, we will try to formulate a working definition, reasoning and articulating facts and preferences of various other authors and practitioners of the field.
In their book Artificial Intelligence: A Modern Approach, authors Russell and Norvig tried to establish a clear classification of the definition of the field into distinct categories based on working definitions from other authors commenting on AI.
Involves cognitive modeling - we have to determine how humans think in a literal sense (explain the inner workings of the human mind, which requires experimental inspection or psychological testing)
Problems: hard to encode informal knowledge into a formal logic system and theorem provers have limitations (if there's no solution to a given logical notation).
For (3.): Turing defined intelligent behavior as the ability to achieve human-level performance in all cognitive tasks, sufficient to fool a human person (Turing Test).
Searle believes that 'mind' emerges from brain functions, but is more than a 'computer program' - it requires intentionality, consciousness, subjectivity and mental causation.
One could go on and claim that these mental events are, in fact, physical events: My decision is neurons firing, but I'm not aware of this - I feel like I made a decision independently from the physical.
When I stand up after having made the decision (mental event), I'm not physically standing up, but my actions cause mental events in my and the bystanders minds - physical reality is an illusion.
Occurs whenever an organism or artificial intelligence is at some current state and does not know how to proceed in order to reach a desired goal state.
We dealt a lot with so called 'state space search' where the problem is to find a goal state or a path from some initial state to a goal state in the state space.
It is helpful to think of the search as building up a search tree - from any given node (state): what are my options to go next (towards the goal), eventually reaching the goal.
For search algorithms, open list usually means the set of nodes yet to be explored and closed list the set of nodes that have already been explored.
In order to direct the search towards the goal, the evaluation function must include some estimate of the cost to reach the closest goal state from a given state.
For CSPs, states in the search space are defined by the values of a set of variables, which can get assigned a value from a specific domain, and the goal test is a set of constraints that the variables must obey in order to make up a valid solution to the initial problem.
- On Friday, January 18, 2019
4. Search: Depth-First, Hill Climbing, Beam
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: Instructor: Patrick Winston This lecture covers algorithms for ..
Node Coloring Problem in Answer Set Prolog
In this video I walk through how to generate the proper answer sets for the node coloring problem, the goal of the program is to assign colors to nodes, ensuring ...
Steepest Ascent Hill Climbing Algorithm in Artificial Intelligence in Hindi
Welcome Guys, we will see Steepest Ascent Hill Climbing Algorithm in Artificial Intelligence in Hindi. Steepest-Ascent Hill climbing: It first examines all the ...
What Do You Mean By Heuristic Search?
What Do You Mean By Heuristic Search? FIND MORE ABOUT What Do You Mean By Heuristic Search? There are heuristics of every general applicability as ...
What Is A Algorithm In Artificial Intelligence?
The algorithm does not specify which is selected the intuitive idea behind generic search algorithm, given a graph, set of start nodes, and goal to incrementally ...
Hill Climbing Algorithm in Artificial Intelligence in Hindi | Hill Climbing in AI
Welcome Guys, we will see hill climbing algorithm in artificial intelligence in Hindi and Advantages and Disadvantages. Hill climbing in artificial intelligence in ...
Lecture - 6 Problem Reduction Search: AND/OR Graphs
Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, I.I.T,kharagpur. For More details on NPTEL visit ...
BFS Romania example
Breadth-First Search algorithm applied on Romania map. Initial node is Arad and target is Bucharest. * Yellow node means city is visited. Whites are only ...
Lecture - 5 Informed Search
Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science and Engineering,I.I.T, Kharagpur .
State Space Search - Introduction
Artificial Intelligence by Prof. Deepak Khemani,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit