Artificial Intelligence Concepts and Problems

Agent, Environment, and State

• Agents interact with their environment through perception and action.
• An agent's state represents its current knowledge and internal configuration.
• Agents use a state function to maintain their current state based on previous states and observations.
• Agents use a transition function to predict the next state based on the current state and chosen action.
• Agents leverage a utility function to assess the desirability of different outcomes.
• An agent's exploration strategy guides its decision-making process to find the best action.
• The best action is typically the one that maximizes the expected utility.

Tower of Hanoi Problem

• The Tower of Hanoi problem is a classic puzzle that involves moving disks between pegs.
• The puzzle demonstrates the concepts of state-space exploration and planning.

Example: Collect and Goal

• The Collect and Goal problem involves collecting balls and reaching a specific goal location.
• The problem requires planning a sequence of actions to efficiently achieve the goal.
• Finding the optimal order of actions for collecting balls is a key aspect of this problem.

Planning: Assumptions and Objectives

• Planning involves defining a set of actions that achieve a desired goal.
• Planning assumes a deterministic environment, meaning actions have predictable outcomes.
• Planning aims to find the most efficient plan, often measured by minimizing the cost or maximizing the utility.

Activity 1: Find a Least-Energy Path

• The activity involves finding a plan that minimizes energy expenditure to reach a goal.
• The state includes variables for position (X, Y) and the actions include movements (Up, Down, Left, Right).
• The utility function should be defined to incentivize minimizing energy consumption.
• Calculating the energy cost for different paths and comparing their utilities help find the optimal plan.

State-Space Exploration

• State-space exploration involves searching through possible states and actions to find a plan that satisfies the goal.
• State-space is a representation of all possible states the agent can be in.
• Planning algorithms, such as search algorithms, are used to explore the state-space and find an optimal path.

Search Algorithms

• Search algorithms are computational procedures for exploring a state-space to find a solution.
• They systematically explore the state-space using strategies such as depth-first search, breadth-first search, or A*.
• The choice of search algorithm depends on the specific problem requirements and available resources.