Step 1: Define events and priors.
Let $A$ = “actual outcomes are the same”, $R$ = “reports same”.
Let $T$ = “tells truth”, $L$ = “lies”.
Given $P(T)=\tfrac{4}{6}=\tfrac{2}{3}$, $P(L)=\tfrac{1}{3}$.
For two fair throws, $P(A)=\tfrac{6}{36}=\tfrac{1}{6}$, $P(A^c)=\tfrac{5}{6}$.
Step 2: Reporting model.
If truthful, the report equals the reality; if lying, the report is the opposite. Hence
\[
P(R|A,T)=1,\; P(R|A^c,T)=0,\qquad
P(R|A,L)=0,\; P(R|A^c,L)=1.
\]
Step 3: Compute $P(R)$ and $P(A\cap R)$.
\[
P(R)=P(T)P(R|A,T)P(A)+P(L)P(R|A^c,L)P(A^c)
=\frac{2}{3} . 1 . \frac{1}{6}+\frac{1}{3} . 1 . \frac{5}{6}
=\frac{7}{18}.
\]
\[
P(A\cap R)=P(T)P(A)P(R|A,T)=\frac{2}{3} . \frac{1}{6} . 1=\frac{1}{9}.
\]
Step 4: Bayes’ rule for the required probability.
\[
P(A\,|\,R)=\frac{P(A\cap R)}{P(R)}=\frac{\tfrac{1}{9}}{\tfrac{7}{18}}=\frac{2}{7}\approx 0.285714\ldots
\]
Rounded to two decimals: $0.29$.
Final Answer:
\[
\boxed{0.29}
\]