Student posts
Brief information about the master thesis from the MPA: 
  • To find a project: talk to teachers, look for posters, search the web. 
  • The project should be CAS (or physics) related, interpreted in a wide sense. The most important thing is that it has a solid scientific or engineering perspective. 
  • You need an examiner at Chalmers (or GU). (GU students need a GU examiner.) 
  • You need a supervisor at Chalmers/GU or elsewhere, such as in a company. (Examiner and supervisor may be the same person for a local Chalmers project.)
  • Typically the project should be registered at the department where the examiner is active. 
  • Before you start, you need to have the registration form signed by me (MPA), and the examiner. There should be a short project plan which is what I need to see to approve it as a CAS thesis. 
  • And don’t forget to fill in the work card (applies to Chalmers students) once you start on the project. This implies attending two other thesis presentations, as well as being and having an opponent. 
  • More information is found at the studentportal Examensarbete
  • If you plan to do a thesis at another department (i.e. not Physics/Applied Physics) local rules may apply. (This is the case for Computer Science/D&IT)

If you have questions or need help, you very welcome to come and see me. /Mats
 
Monday, 30 November 2015 19:59

Split or Steal Game. Game Theory.

Written by

As part of the game theory student seminar our team played the Split-Steal game in class.

Two players with two actions each, Split or Steal. The treasure was comically 2 gingerbread cookies!

Essentially a form of Hawk-Dove game. Hawk: aggressive (escalates conflict) i.e. Steals , Dove: non-aggressive (backs down from escalation) so naturally Splits.

Different strategies / roles

  • Hawk: Aggressive, never retreats.
  • Dove: Defensive, retreats if opponent is aggressive.
  • Bully: Aggressive against defensive opponents. Retreats if opponent is too aggressive.
  • Retaliator: Defensive, but retaliates aggressively if opponent is aggressive.
  • Prober-retaliator: Defensive, but sometimes makes aggressive probes and only reverts to defensive if the response is aggressive. Retaliates aggressively if opponent is aggressive.

CLICK ON THE LINKS BELOW TO WATCH THE VIDEOS OF THE GAME:

 

Final Part of the game:

More parts of the seminar

Part 02

This game can also be seen as a Bayesian game. Information about characteristics or types of the other players (i.e. payoffs) is incomplete in such games. Nature assigns a random variable to each player which could take values of types for each player and associating probabilities (or a probability density function with those types). At least one player is unsure of the type and the payoffs of another player. Players have initial beliefs about the type of each player and can update their beliefs according to Bayes' Rule as play takes place in the game. The belief a player holds about another player's type might change on the basis of the actions they have played. 

In a Bayesian game setting there are three meaningful notions of expected utility: ex post, ex interim and ex ante. 

  • Ex post: Here EU is computed based on all agents’ actual types (rarely feasible as even the game being played maybe unknown at times)
  • Ex interim: Considers the setting in which an agent knows his own type but not the types of the other agents (more practical)
  • Ex ante: In this case the agent does not know anybody’s type including her own

Analysis of the Game:

 

Conclusion of the analysis.

 

 

 

 

My group's project in Humanoid Robotics course (14/15). We used Chabot robot to be controlled over a network (based on a TCP client-server connection), using a Kinect. Therefore, this system could be use to control the robot on-line from another different place. As can be seen in the video, the robot is able to follow all the arm-movements and also recognizes our hands in order to open or close his clamps.

 

 

In the course Humanoid Robotics, my group used genetic algorithms to let a Bioloid robot evolve a walking behaviour. The training phase (evolution) took place in the simulation environment V-REP. The robot is controlled by a CPG (central pattern generator) which was optimized using a genetic algorithm.

Saturday, 21 November 2015 21:12

Revisiting Nash Equilibrium in Prisoner's Dilemma.

Written by

An often confusing aspect of reading the payoff matrix in a game theory setting (at-least for new comers or those delving into the subject after a hiatus) is the confusion between the row players and column players. A more intuitive method maybe to keep track of the process of propensity of movement of player's states (as per moving in the direction of higher utility) using some sort of color coding to see the direction in which they move. The following figure tries to capture the same - and observe the point where the arrows meet is the location of Nash Equilibrium. I know it may seem too formal an approach to bring in a design aspect (colors and arrows), but then game theory itself is a formalism of something most people would say is common sense, intuition so a bit more formalism wont harm - let me know if this becomes more intuitive:

 

Generic background: As is evident a rational agent has clear preferences (i.e. states that he likes) and always chooses to perform the action with the optimal expected outcome for itself from among all feasible actions. A utility function (in the form of the above payoff matrix) is used to map out real world choices to quantitative numbers. These numbers can be seen to be levels of happiness of the agent in those corresponding states. 

Intuitively, a Nash equilibrium is a stable strategy profile: no agent would want to change his strategy if he knew what strategies the other agents were following. Nash equilibria can be strict and weak, depending on whether or not every agent’s strategy constitutes a unique best response to the other agents’ strategies.

 

 

 

Tuesday, 11 August 2015 08:46

Start-up meeting, fall 2015

Written by

New students, welcome to the CAS program!

Come to the start-up meeting on Monday August 31st, 10.15 room FL71 on Chalmers campus Johanneberg.  

 

From Prof. Bernhard Mehlig

I'd like to advertise that there are opportunities for MSc projects in Dynamical Systems in our group. We analyse the dynamics of particles in turbulent flows with dynamical-systems methods, analytically, by computer simulations, and experimentally.

This question has important applications in cloud physics (droplet dynamics in turbulent clouds and rain initiation), astrophysics (planet formation),  biology (plankton dynamics), and industry (fiber suspensions).

Recently we received a grant from the Knut and Alice Wallenberg foundation (https://www.wallenberg.com/kaw/forskning/beviljade-anslag/projektanslag-2014) that will allow us to employ one or two PhD students on this subject from July 2015.

Please email This email address is being protected from spambots. You need JavaScript enabled to view it. if you're interested so that we can arrange a meeting.

Wednesday, 27 August 2014 08:10

Information meeting for new students

Written by

Information meeting for new CAS students 2015, Monday August 31st, 10.15-11.15, room FL71, Origo (Physics) building, Chalmers Johanneberg.

The meeting is intended for both Chalmers and Gothenburg University students. There will be a brief introduction to the program and an opportunity to meet many of the teachers.

Mats Granath, Director of CAS