How can i implement AND-OR graph. which data structure i can use, & which is one best? while reading algorith i read word FUTILITY , what is means of that?
what is AND arc
Answer to your question is in question itself. you can implement AND_OR graph by using data structure GRAPH & TREE. in any language you can simply create tree or graph. & as per algorithm you can write code for it.
futility is like threshold.it is used for checking perticular condition ,it may be distance or anything.
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I'm trying to implement GradCam (https://arxiv.org/pdf/1610.02391.pdf) in tfjs, based on the following Keras Tutorial (http://www.hackevolve.com/where-cnn-is-looking-grad-cam/) and a simple image classification demo from tfjs, similar to (https://github.com/tensorflow/tfjs-examples/blob/master/webcam-transfer-learning/index.js) with a simple dense, fully-connected layer at the end.
However, I'm not able to retrieve the gradients needed for the gradcam computation. I tried different ways to retrieve gradients for the last sequential layer, but did not succeed, as types of tf.LayerVariable from the respective layer is not convertible to the respective type of tf.grads or tf.layerGrads.
Did anybody already succeeded to get the gradients from sequential layer to a tf.function like object?
I'm not aware of the ins and outs of the implementation, but I think something along the lines of this: http://jlin.xyz/advis/ is what you're looking for?
Source code is available here: https://github.com/jaxball/advis.js (not mine!)
This official example in the tfjs-examples repo should be close to, if not exactly, what you want:
https://github.com/tensorflow/tfjs-examples/blob/master/visualize-convnet/cam.js#L49
I need to implement an intelligent agent to play Abalone game, for this kind of game the best way to proceed seems a min-max strategy with alpha beta pruning.
I have already implemented a naive search algorithm that use min-max with pruning,
my problem is...
How to generate the nodes of the tree where perform the search?
I have no idea of the right way to do this, and how assign the weigh to each node.
For generating the tree nodes: You need to implement a method that returns a collection of all possible legal moves given the current board position and the player whose turn it is. All these moves will become children of the node representing the current board position. Repeat until memory is exhausted to generate the game tree ;) or rather until you reach a reasonable tree depth.
For alpha-beta search you also need an evaluation function which calculates the weight for each board position/node. You can do some research or think about such a function yourself, maybe considering the number of stones still on the board. However a bad evaluation function can seriously screw up your results, so take care and run a lot of tests.
If you have trouble coming up with a reasonable evaluation function, I recommend you take a look into Monte-Carlo techniques such as UCT.
http://en.wikipedia.org/wiki/Monte_Carlo_tree_search
These tackle the problem using a probabilistic approach and have some nice advantages over alpha-beta. Also they don't require an evaluation function so you could skip this step.
Good luck!
I have published two libraries for move generation in Abalone. You didn't mention the programming language used for your search implementation, but you can easily port the functions.
For C++, https://sourceforge.net/projects/abnet/
For Python, https://gitlab.com/peer.sommerlund/haliotis
For an evaluation function, distance between all your marbles, or distance to their gravity center (same thing), works nicely. Tino Werner used this with a twist for his program that won ICGA 2003.
For understanding distance when using hex coordinates, I can recommend Amit Patel's page: https://www.redblobgames.com/grids/hexagons/
Need to use c for a project and i saw this screenshot in a pdf which gave me the idea
http://i983.photobucket.com/albums/ae313/edmoney777/Screenshotfrom2013-11-10015540_zps3f09b5aa.png
It say's you can treat each pixel of an image as a graph node(or vertex i guess) so i was wondering how
i would do this using OpenCV and the CvGraph set of functions. Im trying to do this to learn about and how
to use graphs in computer vision and i think this would be a good starting point.
I know i can add a vetex to a graph with
int cvGraphAddVtx(CvGraph* graph, const CvGraphVtx* vtx=NULL, CvGraphVtx** inserted_vtx=NULL )
and the documentation says for the above functions vtx parameter
"Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied)"
is this how i would represent a pixel as a graph vertex or am i barking up the wrong tree...I would love to learn more about
graphs so if someone could help me by maybe posting code, links, or good ol' fashioned advice...Id be grateful=)
http://vision.csd.uwo.ca/code has an implementation on Mulit-label optimization. GCoptimization.cpp file has a GCoptimizationGridGraph class, which I guess is what you need. I am not a C++ expert, so can't still figure out how it works. I am also looking for some simpler solution.
I need to implement Minesweeper solver. I have started to implement rule based agent.
I have implemented certain rules. I have a heuristic function for choosing best matching rule for current cell (with info about surrounding cells) being treated. So for each chosen cell it can decide for 8 surroundings cells to open them, to mark them or to do nothing. I mean. at the moment, the agent gets as an input some revealed cell and decides what to do with surrounding cells (at the moment, the agent do not know, how to decide which cell to treat).
My question is, what algorithm to implement for deciding which cell to treat?
Suppose, for, the first move, the agent will reveal a corner cell (or some other, according to some rule for the first move). What to do after that?
I understand that I need to implement some kind of search. I know many search algorithms (BFS, DFS, A-STAR and others), that is not the problem, I just do not understand how can I use here these searches.
I need to implement it in a principles of Artificial Intelligence: A modern approach.
BFS, DFS, and A* are probably not appropriate here. Those algorithms are good if you are trying to plan out a course of action when you have complete knowledge of the world. In Minesweeper, you don't have such knowledge.
Instead, I would suggest trying to use some of the logical inference techniques from Section III of the book, particularly using SAT or the techniques from Chapter 10. This will let you draw conclusions about where the mines are using facts like "one of the following eight squares is a mine, and exactly two of the following eight squares is a mine." Doing this at each step will help you identify where the mines are, or realize that you must guess before continuing.
Hope this helps!
I ported this (with a bit of help). Here is the link to it working: http://robertleeplummerjr.github.io/smartSweepers.js/ . Here is the project: https://github.com/robertleeplummerjr/smartSweepers.js
Have fun!
I am working on a basic graph implementation(Adj List based) in C so that I can re-use the basic structure to solve all graph related problems.
To map a graph I draw on a paper,I want the best and easiest way.
Talking of the way I take the input rather then how should I go about implementing it! :)
Should I make an input routine which asks for all the nodes label first and then asks for what all edges are to be connected based on two labels?
What could be a good and quick way out? I want an easy way out which lets me spend less amount of energy on the "Input".
Best is to go for input of an edge list,
that is triplets of,
Source, Destination, Cost
This routine can be used to fill Adj List and Adj Matrix.
With the latter, you would need to properly initialize the Matrix though and setup a convention to determine non existent edges.
Here you find details about representation of graph:
Graph-internal-representaion
However here some codes in c++ and java are also given,which you can easily convert to C codes.