Ned Up Middle Down Left 3, 5,6 7 Apu Center 3, 4 7 Right 3 2, 1,0 c. Complete the payoffs of the game table above so that neither player has a strictly dominant strategy, but also Middle is the only rationalizable strategy for Ned and Center is the only rationalizable strategy for Apu. Clearly explain why Up and Down for Ned and Left and Center for Apu are not rationalizable. (Again, there are many equally correct answers.)
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- Q) Given a 3-player game in which coalitions have the following valuesCoalition Gain1 152 303 101.2 601.3 452.3 651,2,3 100Determine the game's Shapley value. Does the Shapley value belong to the core? (you doa direct verification)Given: e-NFA M2 = ({A,B,C}, {0,1}, delta, A, {C}) where delta: (A,0) -> {C}, (A,1) -> {B}, (A,e) -> null, (B,0) -> {A}, (B,1) -> null, (B,e) -> {C}, (C,0) -> null, (C,1) -> {A}, (C,e) -> null. Get the equivalent DFA of the given e-NFA. How many accepting states in the equivalent DFA?How exactly would I be able to paraphrase this pseudo-code so that it can make a bit more sense? 1.Initialtzation: generate a random solution X ← RandomSolution() 2. Solve the traffic assignment problem at equilibrium for each link: (flow, cost) ← NonLinearComplementary(X) 3. Evaluate the objective value for the current solution: f (X) ← EvaluateObj Val (f low, cost) 4. T ← Tmax 5 while (T > Tmin) do 6 I ← 1 7 while (t < ltermax)do 8 X' ← FindNeighborSolution(X) 9 (flow,cost) ← NonLinearComplementary(X') 10 f(X') ← EvaluateObf Val (f low, Cost) 11 Δ ←(f(x) - f(x')) 12 if(Δ<0)then 13 BoltzmannValue ← exp(-Δ/T) 14 if (BoltzmannValue < Random (0,1)) then 15 Accept the new solution: X ← X' 16 end If 17 Else I8 Accept the new solution: X ← X' 19 end if 20 i ← i+1 21 end while 22 T ←T ∞ 23 end while ________
- Write a python code of this problem Problem Statement Assume that there are two teams and they are team attacker and team defender. Therefore, at a state of the game one agent in each team is left alive respectively. Here, the defender is given a lifeline called HP which will be assigned randomly. Furthermore, the attacker agent will try to give maximum negative HP to the defender agent to decrease his(d) chances of survival in the game. On the other hand, the defender agent will try to protect himself by receiving the lowest negative HP possible from the attacker agent. Furthermore, the attacker can have a choice from a number of bullets from his gun and the optimal moves will cost a certain maximum negative HP (chosen from randomly assigned values within the range of minimum and maximum negative HP). Here, are the following things you need to do using Alpha-Beta Pruning algorithm: Sample Input 1: Enter your student id: 17301106 Minimum and Maximum value for the…I meant to say that S -> A -> B -> G is the actual optimal path with cost 7 compared to S -> B -> G which has a path cost of 8. But with the heuristics considered this would be the search: S -> A = 2 + h(A) = 3S -> B = 4 + h(B) = 7From there on, it would lead to S -> A -> B -> G and not S -> B -> G, which is we want to have in this problem. So how is this solved? Since S -> A -> G isn't optimal as it is not possible to reach G without intercepting B.Sorry for the typo earlier.The Manhattan Tourist Problem (1) Given setting in Figure 6.4, calculate exact number of different paths by dynamic programming. (2) For a general setting, i.e., from source(0,0) to sink (n, m), how many different paths by dynamic programming?1 4 3 3 4 1 0 4 3 N 5 1
- Select the appropriate characteristic for each of the following environments Note: The characteristics of the environment are determined using the following shortcuts FO: Fully Observable - PO: partially Observable SA: Single Agent - MA: Multi Agent DT: Deterministic - ST: Stochastic SQ: Sequence - EP: Episodic Backgammon Choose: Bachgammon Po ma st sq Fo sa dt sq Po sa st sq Fo ma st s1 Boker Choose: Bachgammon Po ma st sq Fo sa dt sq Po sa st sq Fo ma st s1 crossword puzzle Choose: Bachgammon Po ma st sq Fo sa dt sq Po sa st sq Fo ma st s1 Medical Diagnostic Choose: Backagammon Po ma st sq Fo sa dt sq Po sa st sq Fo ma st s1Can you find a stable outcome for the following network, if possible. If not, please explain why.a. Given n items, where each item has a weight and a value, and a knapsack that can carry at most W You are expected to fill in the knapsack with a subset of items in order to maximize the total value without exceeding the weight limit. For instance, if n = 6 and items = {(A, 10, 40), (B, 50, 30), (C, 40, 80), (D, 20, 60), (E, 40, 10), (F, 10, 60)} where each entry is represented as (itemIdi, weighti, valuei). Use greedy algorithm to solve the fractional knapsack problem. b. Given an array of n numbers, write a java or python program to find the k largest numbers using a comparison-based algorithm. We are not interested in the relative order of the k numbers and assuming that (i) k is a small constant (e.g., k = 5) independent of n, and (ii) k is a constant fraction of n (e.g., k = n/4). Provide the Big-Oh characterization of your algorithm.
- To achieve consistency, the players have to reach an agreement on the game state.However, this opens a door to distributed consensus problems. Let us look at one ofthem, called the two-generals problem: Two generals have to agree whether to attacka target. They have couriers carrying the messages to and fro, but the delivery of themessage is unreliable. Is it possible for them to be sure that they have an agreementon what do? For a further discussion on consensus problems, see Lamport and LynchShow that the lowest-cost join order can be computed in time O(3n). Assumethat you can store and look up information about a set of relations (such asthe optimal join order for the set, and the cost of that join order) in constanttime. (If you find this exercise difficult, at least show the looser time bound ofO(22n).)You are required to create a Julia program that does the following in this problem:Analyze every policy you are given, then tweak it until a solution is discovered. Real-time recording and saving of the Markov decision process (MDP).