6.xxx (AKA 6.803 and 6.833)

The Human Intelligence Enterprise: Spring 2006

FORSAN ET HAEC OLIM MEMINISSE IUVABIT

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6xxx Projects 2017

Updated 13 April 2017


Anna Sinelnikova

The Effect of Visual Input on Language Learning

If we are to understand language acquisition, then we must understand how the visual system influences our language learning capabilities.

Project type

Pilot Experiment

Steps

Contributions



Dennis Garcia

Reimplementation of Melanoma Recognition Program

In order to take the field of AI to the next level, we need to focus on developing technology to enhance humanity as opposed to finding ways to replace it. One way we can do this is to take AI concepts and apply them to the field of medical diagnosis. A recent example of this is the system Codella, et. al developed to detect melanoma from images. If we are to understand the impact AI can play in medical diagnosis and whether or not the system can be improved, we must reimplement the system described and attempt to make improvements on it.

Project type

Reimplementation

Steps

Contributions



Dillon Dumesnil and Alexander Nordin

Stock Shift Prediction using News Articles

If we can anticipate market movement based on news feeds in real time, then we can garner insight into the way the market reacts to various types of news.

Project type

Research project with implementation.

Steps

Contributions



Emanuele Ceccarelli, Alec Anderson

Game-playing Programs That Explain Themselves

Game-playing programs such as AlphaGo have beaten human experts at complex games previously thought to be computationally intractable. However, these programs tell us little about human intelligence, partially due to their use of neural networks that lack intuitive explanation. If we are to understand how humans play these games, these programs must be able to explain themselves. To simplify this problem, we will restrict our analysis to a simpler game, Checkers, to allow us to develop methods allowing the system to explain its decisions in a human-understandable way.

Project type

Research project with implementation, partially a reimplementation

Steps

Contributions



Houssam Kherraz

Image Recognition - A symbolic AND connectionist approach

If we are to build more human and more powerful image recognition systems, we need to leverage the advantages of both symbolic methods and connectionist ones in a complementary way. This project uses a knowledge representation that would empower connectionist methods like neural nets. “Classes” of objects like ‘cats’ will be represented by different features that might contribute in making a cat a cat. For instance, a cat would be represented by basic features called primitive features like `fur', `hind legs,' `pointy ears,' `tail' etc. Neural networks will be used to recognize these high level features, instead of the object itself. This representation would enable `generalization.' If for example, I train my system to recognize tigers and leopards, then I will need a few examples of Ocelots for my system to start recognizing ocelots. The reason is Ocelots are made of a linear combination of features of tigers and leopards.

Project type

Research project with implementation.

Steps

Contributions



Jessy Lin

Subjective judgments of perceptual and conceptual randomness

People have a peculiar perception of randomness: on one hand, it allows us to pick out statistical regularities and notable patterns from otherwise noisy input (e.g. identifying words in a spoken sentence, even in a noisy environment). On the other, it can be entirely irrational, causing us to see structure where there is none or develop incorrect and biased intuitions. Why are our conscious judgments of randomness often so poorly aligned with reality, even though our perceptual systems have been trained to instinctively extract information from noise? Is our perception of randomness learned through experience? If we are to understand how people perceive structure in noise, we must understand how we interpret both perceptual (e.g. in visual/auditory stimuli) and conceptual (e.g. sequences of coin tosses) randomness.

Project type

Pilot study

Steps

Contributions



Kate Hajash

Collaborative Robots Develop Language for Communication through Games

If we are to create truly autonomous and collaborative robots that operate in dynamic environments, then we must build robots that can understand and develop language based on world experience. This would improve the robot's ability to communicate with one another and their collaborative performance.

Project type

Research project with implementation (overall ambition)

Steps

Contributions



Keith Galli

The Effect of Expressive Gesturing on Memory

If we are to understand the role of our visual system in forming memories, then we need to understand how human gesturing work increases our ability to recall the content later.

Project type

Pilot experiment.

Steps

Contributions



Laura Breiman

Constructive Criticism in Constructing Recipes

If we want to understand how humans construct stories, we need to understand how people understand and respond to feedback and use it to change the story they are telling.

Project type

Research Project

Steps

Contributions



Morgan Voss

Internal and External Models of Self

Human are social beings. If we are to understand human intelligence, then we need to understand how humans view and make inferences about each others personalities.

Project type

Pilot experiment.

Steps

Contributions



Nishchal Bhandari

Intelligent Appearing Videogame AI Using Subsumption Architecture

Most current videogame AI agents do not appear intelligent to players. I suggest using Brooks' subsumption architecture for videogame AI agents to create the appearance of reasonable intelligence.

Project type

Reimplementation and Pilot study

Steps

Contributions



Sailashri Parthasarathy and Katrine Tjoelsen

Human altruism: What happens when one has repeated opportunity to be altruistic?

In order to better understand what makes humans different from other animals, we must understand how humans use symbolic thinking to drive behavior. Humans reason logically with symbolic thinking in a way that other animals don?t. We focus on how humans use symbolic thinking to act altruistically, i.e. selflessly to benefit others. Our approach is to design and run a pilot study to illuminate an aspect of altruistic behavior in humans. The word ?altruism? is used in many contexts, but here we limit ourself to the Merriam-Webster definition: ?[altruism is a] behavior by an animal that is not beneficial to or may be harmful to itself but that benefits others of its species?. Furthermore, we only consider ?altruism? in the context of cash donations given by a human subject to an unknown recipient.

Project type

Pilot study

Steps

Contributions



 

Suri Bandler and Niki Tubacki

Action Based Metaphors in Story Understanding

 If we are to understand how action-metaphors comparing two characters are understood in stories, then we need to understand both how readers derive character traits from actions and how they decide which character traits to apply from metaphors.

Project type

Pilot Experiment

Steps

Contributions



Yan Hao Leon Shen

Universal Representational and Computational Substrate

In order to create systems capable of "understanding" everything and solving any problem, we must create ways of representing and manipulating their knowledge flexibly, integrating different types of knowledge and different strategies for reasoning. Creating a universal substrate for both representation and computation will allow us to achieve this flexibility by capturing rich interconnections between different modalities of "thought".

Project type

Research project

Steps

Contributions

(assuming success)