Lecture

Learning Policies from Non-Traditional Sources

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Description

This lecture explores the concept of learning interactive policies from non-traditional sources of data, focusing on intelligent and interactive autonomous systems. Topics covered include learning latent actions from state-action pairs, language disambiguation, and the use of language-informed latent actions. The lecture delves into the challenges of instruction following in natural language interaction, the development of assistive teleoperation methods, and the implementation of Language-Informed Latent Actions (LILA) for intuitive control mechanisms. Additionally, it discusses the PLATO framework for predicting latent affordances through object-centric pre-interaction and post-interaction phases, showcasing experiments in 2D and 3D manipulation tasks.

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Related concepts (30)

Natural language processing

Natural language processing (NLP) is an interdisciplinary subfield of linguistics and computer science. It is primarily concerned with processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic (i.e. statistical and, most recently, neural network-based) machine learning approaches. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them.

Instruction set architecture

In computer science, an instruction set architecture (ISA), also called computer architecture, is an abstract model of a computer. A device that executes instructions described by that ISA, such as a central processing unit (CPU), is called an implementation. In general, an ISA defines the supported instructions, data types, registers, the hardware support for managing main memory, fundamental features (such as the memory consistency, addressing modes, virtual memory), and the input/output model of a family of implementations of the ISA.

Word-sense disambiguation

Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference.

Instruction pipelining

In computer engineering, instruction pipelining is a technique for implementing instruction-level parallelism within a single processor. Pipelining attempts to keep every part of the processor busy with some instruction by dividing incoming instructions into a series of sequential steps (the eponymous "pipeline") performed by different processor units with different parts of instructions processed in parallel. In a pipelined computer, instructions flow through the central processing unit (CPU) in stages.

Reduced instruction set computer

In computer engineering, a reduced instruction set computer (RISC) is a computer architecture designed to simplify the individual instructions given to the computer to accomplish tasks. Compared to the instructions given to a complex instruction set computer (CISC), a RISC computer might require more instructions (more code) in order to accomplish a task because the individual instructions are written in simpler code.

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