Short-term memory

Definition

Short-term memory refers to the capacity for holding a small amount of information in an active, readily available state for a brief period of time, usually around 20 to 30 seconds. It plays a crucial role in various optimization techniques, where temporary solutions are evaluated and adjusted to find an optimal outcome. This type of memory allows for quick processing and manipulation of data, which is essential in methods like simulated annealing and tabu search, as they rely on maintaining a limited amount of relevant information while exploring potential solutions.

5 Must Know Facts For Your Next Test

1. Short-term memory can typically hold about 7±2 items at once, which means it has limitations in capacity when evaluating potential solutions.
2. In simulated annealing, short-term memory is used to keep track of recent solutions and their associated costs to inform future decisions about exploring new configurations.
3. Tabu search enhances short-term memory by maintaining a list of recently visited solutions to prevent cycling back to them, ensuring a more diverse search of the solution space.
4. The effective use of short-term memory can improve the efficiency of both simulated annealing and tabu search by enabling quicker evaluations and adjustments of the current solution.
5. Short-term memory relies on working memory processes that allow optimization algorithms to maintain relevant information dynamically as they search for better solutions.

Review Questions

• How does short-term memory influence the effectiveness of optimization algorithms like simulated annealing?
  • Short-term memory influences the effectiveness of simulated annealing by allowing the algorithm to retain recent solutions and their costs, facilitating quick evaluations during the search process. This enables the algorithm to make informed decisions about whether to accept new solutions based on their relative merit. By leveraging short-term memory, simulated annealing can avoid unnecessary recalculations and focus on exploring more promising areas within the solution space.
• Discuss the role of short-term memory in preventing stagnation during a tabu search optimization process.
  • In a tabu search optimization process, short-term memory is crucial for maintaining a list of recently explored solutions, which helps prevent stagnation by avoiding cycles back to previously evaluated states. This short-term memory component ensures that the algorithm explores new areas of the solution space, thereby enhancing its ability to escape local optima. By utilizing this memory effectively, tabu search can navigate towards more optimal solutions while keeping track of previous attempts.
• Evaluate how the limitations of short-term memory can affect the outcomes in simulated annealing and tabu search methodologies.
  • The limitations of short-term memory can significantly impact outcomes in both simulated annealing and tabu search methodologies by constraining the amount of information available for decision-making. If too many potential solutions are lost due to limited capacity, the algorithms may overlook better configurations or fail to recognize patterns that could guide them toward optimal solutions. Additionally, insufficient short-term memory might lead to repeated exploration of less favorable areas in the solution space, hindering progress and efficiency. Thus, understanding and optimizing the use of short-term memory is essential for achieving better results in these optimization techniques.

Related terms

Working Memory: Working memory is a cognitive system that temporarily holds and manipulates information needed for complex tasks such as learning, reasoning, and comprehension.

Heuristic: A heuristic is a problem-solving approach that employs a practical method or various shortcuts to produce solutions that may not be optimal but are sufficient for reaching an immediate goal.

State Space: State space is the set of all possible states or configurations that can be achieved in a given optimization problem, often explored during the search for an optimal solution.