reinforcement


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@machinelearnbot

I am having a hard time making a machine suffer. Strengthening learning of a machine by giving it negative feedback is tricky. But then it is debatable if all humans learn alike from rewards/punishments:\ And that is why we stay enamored by kids. How do they learn what they learn? They never knew the language before; they never knew any of the concepts of this world before.


Under the Hood with Reinforcement Learning – Understanding Basic RL Models

@machinelearnbot

Summary: Reinforcement Learning (RL) is likely to be the next big push in artificial intelligence. It's the core technique for robotics, smart IoT, game play, and many other emerging areas. But the concept of modeling in RL is very different from our statistical techniques and deep learning. In this two part series we'll take a look at the basics of RL models, how they're built and used. In the next part, we'll address some of the complexities that make development a challenge.


Playing the Beer Game Using Reinforcement Learning

@machinelearnbot

The beer game is a widely used in-class game that is played in supply chain management classes to demonstrate a phenomenon known as the bullwhip effect. The game consists of a serial supply chain network with four players--a retailer, a wholesaler, a distributor, and a manufacturer. In each period of the game, the retailer experiences a random demand from customers. Then the four players each decide how much inventory of "beer" to order. The retailer orders from the wholesaler, the wholesaler orders from the distributor, the distributor from the manufacturer, and the manufacturer orders from an external supplier that is not a player in the game.


artifical-intelligence-and-creativity-imagining-the-unimaginable

#artificialintelligence

How artificial intelligence can be used creatively is an often asked, and perpetually unsolved, question. Of course, the term "AI" itself can be somewhat misleading; serving, as it does, as a catch-all phrase for anything involving machine learning and/or algorithms. What is possible, however, is to explore in general terms what levels of creativity we can currently see from the people and technology working in this space. Beginning with the most publicised stories, we have IBM's lighthouse project Watson, which created a movie trailer for the film "Morgan", (a film about an artificially intelligent robot child – spoiler alert: it doesn't go well), and Sony using a system of machine learning algorithms called "Flow Machines" to compose a pop song, ("Daddy's Car"). Further back, we also had Oscar Sharp and Ross Goodwin put a recurrent neural network to work writing a screenplay for a film called "Sunspring", which they subsequently shot in a single day, (it is a must-watch).


Machine Learning for grandmas

#artificialintelligence

Machine Learning is hard to define and may mean different things but everybody will probably agree that it is an Artificial Intelligence subfield. AI means intelligence exhibited by machines. In Machine Learning, we teach machines to do things. What machines learn allows them to make smart decisions later on. However machines do not learn like us (at least for now), so we teach them through data.


Embodied Intelligence Wants to Teach Robots With Virtual Reality

WIRED

Do me a favor and grab and object near you. Even if it's something you've never handled before, odds are your brain automatically worked out how you should grasp the thing and with what force. It's the kind of clever dexterity that makes you human. Ask a robot to do the same and you'll either get a blank stare or a crumpled object in the cold, cold grasp of a machine. Because robots are good at repetitive tasks that require a lot of strength, but they're still bad at learning how to manipulate novel objects.


Why Montreal Has Emerged As An Artificial Intelligence Powerhouse

#artificialintelligence

Yoshua Bengio is one of the foremost thinkers in a field within artificial intelligence known as artifical neural networks and deep learning. Although significant progress has been made in recent years due to (among other factors) the combination of the proliferation of data, the decreasing cost of compute, and the tremendous amount of money and talent now devoted to artificial intelligence, Bengio chose this as a field of study during the 1980s, in the throes of what some referred to as the AI winter, seeing through a period when money and enthusiasm for artificial intelligence had dried up. Bengio is the co-author (with Ian Goodfellow and Aaron Courville) of Deep Learning, a book that Elon Musk referred to as "the definitive textbook on deep learning." On top of his growing influence in this field, he has also been enormously influential in shaping Montreal to become a hotbed for artificial intelligence. Bengio co-founded Element AI in 2016, which has a stated mission to "turn the world's leading AI research into transformative business applications."


Why Montreal Has Emerged As An Artificial Intelligence Powerhouse

#artificialintelligence

Yoshua Bengio is one of the foremost thinkers in a field within artificial intelligence known as artifical neural networks and deep learning. Although significant progress has been made in recent years due to (among other factors) the combination of the proliferation of data, the decreasing cost of compute, and the tremendous amount of money and talent now devoted to artificial intelligence, Bengio chose this as a field of study during the 1980s, in the throes of what some referred to as the AI winter, seeing through a period when money and enthusiasm for artificial intelligence had dried up. Bengio is the co-author (with Ian Goodfellow and Aaron Courville) of Deep Learning, a book that Elon Musk referred to as "the definitive textbook on deep learning." On top of his growing influence in this field, he has also been enormously influential in shaping Montreal specifically and Canada more generally has become a hotbed for artificial intelligence. Bengio co-founded Element AI in 2016, which has a stated mission to "turn the world's leading AI research into transformative business applications."


Artificial Intelligence: Google's DeepMind learned without human input - Content Loop

#artificialintelligence

Google's DeepMind Artificial Intelligence AlphaGo Zero recently attained an important milestone--the Artificial Intelligence (AI) taught itself how to play the strategy game Go without any human interaction and was able to beat the world's best Go players. The ability to reach this level of performance with human input is a significant step forward in the maturation of AI. Over the past several years, AI has made significant progress in a wide variety of areas such as image and speech recognition, drug discovery, and algorithmic trading. In most of these cases, the AI relies on vast existing data sets and some degree of human engagement. A long-standing ambition of AI researchers has been to create algorithms that do not rely on already existing data sets nor the need for human input.


God of Go: The Rise of Superhuman Intelligence Without Human Knowledge - The Wire

#artificialintelligence

Siby Abraham is a computer scientist specialising in artificial intelligence. He is an associate professor and head of the department of mathematics and statistics at Guru Nanak Khalsa College, Mumbai. How many years does it take for a child that does not know anything about English to master it at a Shakespearean level? Assume that there is no one to teach the child, and that the child only knows about the fundamentals of English grammar to begin with. Suppose also that there is no book, no help and no support (human or non-human) at all times.