Artificial Intelligence Tutorial

Introduction to Artificial Intelligence Intelligent Agents

Search Algorithms

Problem-solving Uninformed Search Informed Search Heuristic Functions Local Search Algorithms and Optimization Problems Hill Climbing search Differences in Artificial Intelligence Adversarial Search in Artificial Intelligence Minimax Strategy Alpha-beta Pruning Constraint Satisfaction Problems in Artificial Intelligence Cryptarithmetic Problem in Artificial Intelligence

Knowledge, Reasoning and Planning

Knowledge based agents in AI Knowledge Representation in AI The Wumpus world Propositional Logic Inference Rules in Propositional Logic Theory of First Order Logic Inference in First Order Logic Resolution method in AI Forward Chaining Backward Chaining Classical Planning

Uncertain Knowledge and Reasoning

Quantifying Uncertainty Probabilistic Reasoning Hidden Markov Models Dynamic Bayesian Networks Utility Functions in Artificial Intelligence

Misc

What is Artificial Super Intelligence (ASI) Artificial Satellites Top 7 Artificial Intelligence and Machine Learning trends for 2022 8 best topics for research and thesis in artificial intelligence 5 algorithms that demonstrate artificial intelligence bias AI and ML Trends in the World AI vs IoT Difference between AI and Neural Network Difference between Artificial Intelligence and Human Intelligence Virtual Assistant (AI Assistant) ARTIFICIAL INTELLIGENCE PAINTING ARTIFICIAL INTELLIGENCE PNG IMAGES Best Books to learn Artificial Intelligence Certainty Factor in AI Certainty Factor in Artificial Intelligence Disadvantages of Artificial Intelligence In Education Eight topics for research and thesis in AI Engineering Applications of Artificial Intelligence Five algorithms that demonstrate artificial intelligence bias 6th Global summit on artificial intelligence and neural networks Acting Humanly In Artificial Intelligence AI and ML Trends in the World AI vs IoT Artificial Communication Artificial intelligence assistant operating system Artificial Intelligence in Pharmacy Artificial Intelligence in Power Station Artificial Intelligence in Social Media Artificial Intelligence in Supply Chain Management Artificial Intelligence in Transportation Artificial Intelligence Interview Questions and Answers Artificial Intelligence Jobs in India For Freshers Integration of Blockchain and Artificial Intelligence Interesting Facts about Artificial Intelligence Machine Learning and Artificial Intelligence Helps Businesses Operating System Based On Artificial Intelligence SIRI ARTIFICIAL INTELLIGENCE SKILLS REQUIRED FOR ARTIFICIAL INTELLIGENCE Temporal Models in Artificial Intelligence Top 7 Artificial Intelligence and Machine Learning trends for 2022 Types Of Agents in Artificial Intelligence Vacuum Cleaner Problem in AI Water Jug Problem in Artificial Intelligence What is Artificial Super Intelligence (ASI) What is Logic in AI Which language is used for Artificial Intelligence Essay on Artificial Intelligence Upsc Flowchart for Genetic Algorithm in AI Hill Climbing In Artificial Intelligence IEEE Papers on Artificial Intelligence Impact of Artificial Intelligence On Everyday Life Impact of Artificial Intelligence on Jobs The benefits and challenges of AI network monitoring

Heuristic Functions in Artificial Intelligence
2019-07-16 12:24:59

Heuristic Functions in Artificial Intelligence

Heuristic Functions in AI: As we have already seen that an informed search make use of heuristic functions in order to reach the goal node in a more prominent way. Therefore, there are several pathways in a search tree to reach the goal node from the current node. The selection of a good heuristic function matters certainly. A good heuristic function is determined by its efficiency. More is the information about the problem, more is the processing time.

Some toy problems, such as 8-puzzle, 8-queen, tic-tac-toe, etc., can be solved more efficiently with the help of a heuristic function. Let’s see how:

Consider the following 8-puzzle problem where we have a start state and a goal state. Our task is to slide the tiles of the current/start state and place it in an order followed in the goal state. There can be four moves either left, right, up, or down. There can be several ways to convert the current/start state to the goal state, but, we can use a heuristic function h(n) to solve the problem more efficiently.

heuristic function for the 8-puzzle problem

A heuristic function for the 8-puzzle problem is defined below:

h(n)=Number of tiles out of position.

So, there is total of three tiles out of position i.e., 6,5 and 4. Do not count the empty tile present in the goal state). i.e. h(n)=3. Now, we require to minimize the value of h(n) =0.

We can construct a state-space tree to minimize the h(n) value to 0, as shown below:

heuristic function for the 8-puzzle problem 2

It is seen from the above state space tree that the goal state is minimized from h(n)=3 to h(n)=0. However, we can create and use several heuristic functions as per the reqirement. It is also clear from the above example that a heuristic function h(n) can be defined as the information required to solve a given problem more efficiently. The information can be related to the nature of the state, cost of transforming from one state to another, goal node characterstics, etc., which is expressed as a heuristic function.

Properties of a Heuristic search Algorithm

Use of heuristic function in a heuristic search algorithm leads to following properties of a heuristic search algorithm:

  • Admissible Condition: An algorithm is said to be admissible, if it returns an optimal solution.
  • Completeness: An algorithm is said to be complete, if it terminates with a solution (if the solution exists).
  • Dominance Property: If there are two admissible heuristic algorithms A1 and A2 having h1 and h2 heuristic functions, then A1 is said to dominate A2  if h1 is better than h2 for all the values of node n.
  • Optimality Property: If an algorithm is complete, admissible, and dominating other algorithms, it will be the best one and will definitely give an optimal solution.