MSC: HIS2011 Registration Payment Method

Note to self:  Payment method for HIS 2011


METHOD 3: Payment by wire transfer (For Local Participants Only):
Please send the payment instruction to BIMBMYKL by SWIFT with the following details:
Payment amount: Please mention the exact amount. Please pay all costs/bank transfer fees etc, so that the conference account gets the full amount.
Reimbursement instruction: HIS 2011 and paper ID

Beneficiary bank's name: Bank Islam Malaysia Berhad (Cawangan Bandar Melaka)
Beneficiary bank's address: No. 50, Jalan Cempaka 1, Taman Cempaka, Peringgit, 75400 Melaka, Malaysia.
Benificiary's account number: 04-015-01-004888-6
Benificiary's name: Universiti Teknikal Malaysia Melaka

MSC: TODO: Conference Registration

So, the registration fee for the HIS 2011 conference in Melacca is $400 ≈ RM1240

Sign Copyright form

Revise paper:
Add a flow chart the size of Fig.2
Take out unnecessary citations.
Put Fig 3 & 9 can be put together, and smaller.
Comparisons will be done in future work.

MSC: HIS2011 Accepted Paper 1

Below are the comments I received from my reviewers of the paper, which I recently submitted to HIS 2011.

PAPER: 159
TITLE: Evolutionary Spiking Neural Networks as Racing Car Controllers
AUTHORS: Elias Yee and Jason Teo

REVIEW 1

OVERALL RATING: 1 (weak accept)
REVIEWER'S CONFIDENCE: 4 (expert)
How relevant is this manuscript for HIS 2011 attendees? Please explain under Public Comments:: 4 (good)
Is the manuscript technically sound? Please explain your answer under Public Comments:: 4 (good)
How would you rate the organization of the manuscript? Is it focused? Is the length appropriate for the topic?: 3 (fair)
Please rate the readability of the manuscript. Explain your rating under Public Comments below:: 3 (fair)

This paper employs evolutionary programming to improve the control of open racing car simulator. It is interesting.

However, several revisions should be done. First, lots of cited references are lost in reference list, such as Figueira and Roque (2011), Vázquez and Garro (2011), Daun-Gruhn and Büschges (2011), Munoz, Gutierrez, and Sanchis (2010), and Jakobsen (2007).

Secondly, please clearly introduce of your models and provide some necessary figures or flowchart with some essential brief explanation vis-à-vis the text to understand the implementing procedure.

Finally, please provide some necessary comparison among the proposed model and other alternatives.


REVIEW 2

OVERALL RATING: 2 (accept)
REVIEWER'S CONFIDENCE: 2 (medium)
How relevant is this manuscript for HIS 2011 attendees? Please explain under Public Comments:: 4 (good)
Is the manuscript technically sound? Please explain your answer under Public Comments:: 4 (good)
How would you rate the organization of the manuscript? Is it focused? Is the length appropriate for the topic?: 4 (good)
Please rate the readability of the manuscript. Explain your rating under Public Comments below:: 4 (good)

Interesting paper

MSC: Experiment running on all 5 PCs in Lab

Set up all 5 PCs to run experiments now. Will start Experiment on track 2 tonight or tomorrow morning.

Plan to meet Dr James tomorrow, Oct 7, Friday.

Write Paper 2!!

MSC: Text from - izhikevich and ffnn docx

Below is the copy-pasted text from the document "izhikevich and ffnn.docx"

Reason for pasting it here is so that I could delete that doc file and refer to the text here.

Abstract

The Izhikevich spiking neural network model is investigated as a method to develop controllers for a simple, but not trivial, car racing game, called TORCS. The controllers are evolved using the Evolutionary Strategy, and the performance of the best individuals are compared with the hand-coded controller included with the game.

racing competition is a wat wat wat, and since networks of spiking neurons have been gaining popularity in recent years, a great curiosity emerged to want to find out if a spiking neural network could perform as well or better than the other techniques used to train the driver. This paper investigates the performance of the Izhikevich spiking neural network model applied to the TORCS racing game, and trained using Evolutionary Strategy. The evolved driver is compared with the hand-coded driver included in the TORCS championship platform.

Introduction

Many methods have been used to optimize the TORCS game driver for the cig competition, curious if spiking neural network could also perform well in it. Hence, compared the network with the simple driver provided with the competition client.

Results – the spiking neural network does perform better.

Machine learning methods can be used to solve any simulated control problems. In this paper, an evolutionary optimization technique is used to evolve a controller to drive a simulated racing car. The car control is handled by an artificial neural network, using Evolutionary Strategies for the tuning of the weights. Different experiments are run in order to explore combinations of training parameters.

MSC: Torcs Suprisingly Runs on Vista - Finally

Tried running the experiment of Sigmoidal ANN on PC2's native OS, Vista, and surprisingly returned no error. Will duplicate it and run the experiment on PC3 and PC5, which also runs Vista.