In computer science, an action language is a language for specifying state transition systems, and is commonly used to create formal models of the effects of actions on the world. Action languages are commonly used in the artificial intelligence and robotics domains, where they describe how actions affect the states of systems over time, and may be used for automated planning. Action languages fall into two classes: action description languages and action query languages. Examples of the former include STRIPS, PDDL, Language A (a generalization of STRIPS; the propositional part of Pednault's ADL), Language B (an extension of A adding indirect effects, distinguishing static and dynamic laws) and Language C (which adds indirect effects also, and does not assume that every fluent is automatically "inertial"). There are also the Action Query Languages P, Q and R. Several different algorithms exist for converting action languages, and in particular, action language C, to answer set programs. Since modern answer-set solvers make use of boolean SAT algorithms to very rapidly ascertain satisfiability, this implies that action languages can also enjoy the progress being made in the domain of boolean SAT solving. (Wikipedia).
Introduction to the C programming language. Part of a larger series teaching programming. See http://codeschool.org
From playlist The C language
Introduction to the C programming language. Part of a larger series teaching programming. See http://codeschool.org
From playlist The C language
From playlist Classroom Activities for Active Learning
Assembly language (ASM) is not a mythical dark art, in fact it's fundamental to computers operating at all. I take a quick look at a very simple assembly language and show where it fits in.
From playlist Interesting Programming
The C programming language (unit 2) - 4 of 5 (old version; watch new version instead)
A continuation of discussing the C programming language. This unit goes more into depths on pointers and arrays. Visit http://codeschool.org
From playlist The C language (unit 2)
Scripting vs Programming :Major Difference Between Scripting And Programming | #Shorts | Simplilearn
🔥Explore Our Free Courses With Completion Certificate by SkillUp: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=ScriptingvsProgramming&utm_medium=ShortsDescription&utm_source=youtube A scripting language is a computer language that does not require compilation and i
From playlist #Shorts | #Simplilearn
Clojure - the Reader and Evaluator (4/4)
Part of a series teaching the Clojure language. For other programming topics, visit http://codeschool.org
From playlist the Clojure language
Clojure - the Reader and Evaluator (2/4)
Part of a series teaching the Clojure language. For other programming topics, visit http://codeschool.org
From playlist the Clojure language
Assembly Language Tutorial 3 : Assembly Language Functions
Code & Transcript Here : http://goo.gl/bmPsYT Support me on Patreon : https://www.patreon.com/derekbanas In this tutorial we will finally create a Real Assembly Language Program! We will learn about Stacks, How to Use C Functions and How to Create Custom Functions in Assembly Language. A
From playlist Assembly Language
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents (+Author)
#gpt3 #embodied #planning In this video: Paper explanation, followed by first author interview with Wenlong Huang. Large language models contain extraordinary amounts of world knowledge that can be queried in various ways. But their output format is largely uncontrollable. This paper inve
From playlist Papers Explained
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances (SayCan - Paper Explained)
#saycan #robots #ai Large Language Models are excellent at generating plausible plans in response to real-world problems, but without interacting with the environment, they have no abilities to estimate which of these plans are feasible or appropriate. SayCan combines the semantic capabil
From playlist Papers Explained
Stanford Seminar - Mind in Motion: How Action Shapes Thought
Barbara Tversky Columbia University January 10, 2020 All creatures must move and act in space to survive. Spatial thinking is the foundation of thought, not the entire edifice, but the foundation. The same brain structures that represent places and spatial relations also represent people,
From playlist Stanford Seminars
CICERO: An AI agent that negotiates, persuades, and cooperates with people
#ai #cicero #diplomacy A team from Meta AI has developed Cicero, an agent that can play the game Diplomacy, in which players have to communicate via chat messages to coordinate and plan into the future. Paper Title: Human-level play in the game of Diplomacy by combining language models
From playlist Papers Explained
Rasa Reading Group: Template Guided Text Generation for Task-Oriented Dialogue
This week we'll be starting a new paper: "Template Guided Text Generation for Task-Oriented Dialogue" by Mihir Kale and Abhinav Rastogi from EMNLP 2020. Link to paper: https://www.aclweb.org/anthology/2020.emnlp-main.527.pdf
From playlist Rasa Reading Group
modeling adaptive communication games - Sida Wang
Short talks by postdoctoral members Topic: modeling adaptive communication games Speaker: Sida Wang Affiliation: Member School of Mathematics Date: Oct 5, 2018 For more video please visit http://video.ias.edu
From playlist Mathematics
Rasa Livecoding: Handling Toxic Language
(Warning: this stream will contain toxic language.) Now we've got some user-provided data to work with and it's time to start improving our assistant. First up: handling toxic language. What's livecoding? It's folks working on real projects in real time with help from you, the audience! E
From playlist Live Coding
Can Wikipedia Help Offline Reinforcement Learning? (Paper Explained)
#wikipedia #reinforcementlearning #languagemodels Transformers have come to overtake many domain-targeted custom models in a wide variety of fields, such as Natural Language Processing, Computer Vision, Generative Modelling, and recently also Reinforcement Learning. This paper looks at th
From playlist Papers Explained
David Ben-Zvi - Between Coherent and Constructible Local Langlands Correspondences
(Joint with Harrison Chen, David Helm and David Nadler.) Refined forms of the local Langlands correspondence seek to relate representations of reductive groups over local fields with sheaves on stacks of Langlands parameters. But what kind of sheaves? Conjectures in the spirit of Kazhdan
From playlist 2022 Summer School on the Langlands program
Programming Languages - (part 5 of 7)
How source code becomes a running program, how languages are categorized, and a survey of important languages. Part of a larger series teaching programming. Visit http://codeschool.org
From playlist Programming Languages
In this module, we consider whether syntax has an effect on thought, focusing especially on: (i) how the order of the information given in sentences can affect thought, (ii) a study involving Chinese, Japanese and English speakers, that suggests that Japanese speakers use more cognitive re
From playlist English Language