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Cognitive Learning01:21

Cognitive Learning

426
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
426
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

877
Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
877
Long-Term Memory01:18

Long-Term Memory

206
Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
206
System of Memory01:23

System of Memory

6.3K
Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
6.3K
Long-term Potentiation01:35

Long-term Potentiation

55.4K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
55.4K
Understanding Memory01:19

Understanding Memory

544
Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...
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Lifelong Learning With Cycle Memory Networks.

Jian Peng, Dingqi Ye, Bo Tang

    IEEE Transactions on Neural Networks and Learning Systems
    |July 28, 2023
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    Summary
    This summary is machine-generated.

    This study introduces Cycle Memory Networks (CMNs) to solve anterograde forgetting in lifelong learning agents. CMNs enable continuous learning by separating short-term and long-term memories, facilitating knowledge transfer and accumulation without data storage.

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    Area of Science:

    • Artificial Intelligence
    • Machine Learning
    • Neuroscience

    Background:

    • Lifelong learning is crucial for artificial general intelligence.
    • Existing lifelong learning methods primarily address catastrophic forgetting.
    • Data-free frameworks face anterograde forgetting, where preserving past knowledge hinders new learning.

    Purpose of the Study:

    • To explore knowledge-transferable lifelong learning without historical data storage or significant computational overhead.
    • To address the fundamental issue of anterograde forgetting in lifelong learning.
    • To propose a novel framework inspired by complementary learning theory.

    Main Methods:

    • Proposed Cycle Memory Networks (CMNs) with separate short-term and long-term memory networks.
    • Implemented a transfer cell for knowledge transfer between memory networks.
    • Introduced a memory consolidation mechanism for knowledge accumulation.
    • Evaluated CMNs on various benchmarks including task-related, task-conflict, class-incremental, and cross-domain datasets.

    Main Results:

    • CMNs effectively mitigate anterograde forgetting.
    • The framework demonstrated successful knowledge transfer and accumulation.
    • Performance was validated across diverse lifelong learning scenarios.
    • Ablation studies confirmed the efficacy of individual framework components.

    Conclusions:

    • Cycle Memory Networks offer a robust solution to anterograde forgetting in lifelong learning.
    • The proposed architecture enables continuous learning while facilitating knowledge transfer and preventing conceptual confusion.
    • This work advances the development of artificial general intelligence by improving lifelong learning capabilities.